STAR Webinar - December 20th, 2012 Stroke POpulation Risk Tool.

Slides:



Advertisements
Similar presentations
©2010 Information Age Publishing 1 The Violence Volcano Chapter 1 How Workplace Violence Has Grown.
Advertisements

What’s New in Type 2 Diabetes? Lots!
Generation R Study Claudia Kruithof, MSc datamanager Generation R EUCCONET workshop june 2011 – Record Linkage.
Ten years of the CHD NSF Professor Roger Boyle CBE National Director for Heart Disease and Stroke Department of Health.
The Mental Health of Immigrants and Minorities in Canada - The Social and Economic Effects M. Annie Xu (HRSDC/UNB) Metropolis Brown Bag Seminar July 13,
What is “Go RED for Women?”
June 25, 2006 Propensity Score Adjustment in Survival Models Carolyn Rutter Group Health Cooperative AcademyHealth, Seattle WA.
THE COMMONWEALTH FUND Source: McCarthy and Leatherman, Performance Snapshots, Percentage of Community-Dwelling Adults Ages.
Heart Disease and Stroke Statistics 2011 Update 1.
Presenter Name(s) Issue date National Student.
11 Liang Y. Liu, Ph.D. Community Mental Health & Substance Abuse Services Section Texas Department of State Health Services
Changes in access to the government surveys Labour Force Survey/Annual Population Survey user meeting Welcome.
SC968: Panel Data Methods for Sociologists
County-level Estimates of Leisure Time Physical Inactivity among Adults aged 20 years old Trends
ROBERT D. KERNS, PH.D. NATIONAL PROGRAM DIRECTOR FOR PAIN MANAGEMENT
New Insights about Beef and Heart Health February 2012.
EU Market Situation for Eggs and Poultry Management Committee 21 June 2012.
Meredith Cook Mercer COPHS August,2012. Total Cholesterol HDL Could CVD prediction be improved by also assessing additional lipid-related markers (replacing.
County-level Estimates of Diagnosed Diabetes Incidence among Adults aged ≥ 20 years old Trends
Chris Bonnett, MHSc, PhD (Cand.) H3 Consulting, Guelph Managing Chronic Disease Can it work at work?
Hit and Miss: A Study of Post-Release Support Brendan Quinn and Amy Kirwan 23 rd June 2009.
Statistical Analysis SC504/HS927 Spring Term 2008
COMPUTER B Y : L K. WINDOWS INFORMATION B Y : L K.
TOWARDS UNIVERSAL ACCESS
Source: Financial Times of London Global Banks 1999 – 2009 “Changing of the Guard”
Name ____________________ Date ___________ Period ____.
Nationally representative telephone surveys conducted by Gallup, targeting approximately 2000 English-speaking women ages each year. Margin of error.
Family Relationships Services (FRSA) Thursday, 6 November 2014 Alwin Chong It takes a community to raise a child.
County-level Estimates of Diagnosed Diabetes among Adults aged ≥ 20 years: United States 2004
1 Cervical Screening Programme, England, : Graphs.
UK Renal Registry 17th Annual Report Figure 5.1. Trend in one year after 90 day incident patient survival by first modality, 2003–2012 cohorts (adjusted.
©2013 Australian Indigenous HealthInfoNet 1 Key facts Overview of the health of Indigenous people in Western Australia 2013.
Thu. 3 June An empirical study of the “healthy immigrant effect” with Canadian Community Health Survey Yimin (Gloria) Lou, M.A. Candidate University.
Updated December 2005 PREVENT DIABETES AND HEART DISEASE Enjoy a healthy lifestyle and improve your health 1.
Smoking related disease risk, deprivation and lifestyle behaviours Barbara Eberth (with D Olajide, A Ludbrook, P Craig, & D Stockton)
Inequalities in Health: Lifestyle Factors.
Alcohol Consumption, Life Course Transitions and Health in Later Life Research Team: Keele UniversityUniversity College of London Clare Holdsworth, PINicola.
Center for Disease Control and Prevention National Center for Health Statistics National Health Interview Survey Source: Centers for Disease Control and.
Journal Club Alcohol and Health: Current Evidence July–August 2004.
Preconception Education in the Workplace Presented at the Third National Summit on Preconception Health and Health Care Steve Abelman Director, Educational.
Differences in Education, Internet Access, Health Status, and Health-Related Behaviors Among nonHispanic White, Black, and Latino Members Ages and.
N ENGL J MED MAY 17, , 2012 ASSOCIATION OF COFFEE DRINKING WITH TOTAL AND CAUSE-SPECIFIC MORTALITY Neal D. Freedman, Ph.D., Yikyung Park, Sc.D.,
Quick Questions 1. 1.List statistics that highlight Glasgow’s special health problems. 2.Explain why it is important not to stereotype all people who live.
Deep Dive Case Study Healthy Heart Check (NHS Health Check)
1 Population Health Model (POHEM) AMI Acknowledgements: CCORT for collaboration and funding.
Projecting Future Mortality Using Information on Health Behaviors David M. Cutler, Edward L. Glaeser, and Allison B. Rosen.
Improving the Quality of Physical Health Checks
Using Alcohol & Other Drugs Health Psychology PSCY 4080 Amber M. Henslee, M.S.
Why should I care? Heart Disease is the #1 cause of death in the United StatesHeart Disease is the #1 cause of death in the United States Heart disease.
Coffee Consumption and Risk of Myocardial Infarction among Older Swedish Women SA Rosner, A Akesson,MJ. Stampfer, A Wolk; AJE; :
1 Hypertension Overview. 2 Leading Risks For Death (World Health Organization 2002) Cholesterol Alcohol HYPERTENSION Tobacco use Overweight.
Lesson Starter Health inequalities are result of poor lifestyle CHOICES rather than poor lifestyle CHANCES. Do you agree with this statement? Why/ why.
 Alcohol thins your blood so less blood clots  Alcohol also helps with stress.
Keep Well Evidence from the Keep Well programme in NHS Grampian – 2008 to 2014 Jackie Fleming Keep Well Information Analyst.
Agenda Introduction Model purpose Overall plan Schema Discussion Next Steps.
Why Stroke Surveillance in the English speaking Caribbean ? Dr. Glennis Andall-Brereton Epidemiologist Caribbean Epidemiology Centre (CAREC/PAHO/WHO)
Health expectancy in Denmark 3 rd Meeting of the Task Force on Health Expectancies Luxembourg, 12 December 2006 Henrik Brønnum-Hansen Secular trends Social.
Coffee and Cardiovascular Disease
Healthy Women Healthy Lives March 18, 2014 Healthy in America in 2014 and Beyond.
Alcohol and Health: What Is the Problem? National Center for Injury Prevention and Control Centers for Disease Control and Prevention Cutting Back: A Sensible.
NODE 0 mRS 0: 13.6% (n=551) mRS 1: 19.4% (n=785) mRS 2: 14.7% (n=597) mRS 3: 16.5% (n=668) mRS 4: 21.1% (n=855) mRS 5: 7.0% (n=324) mRS 6: 6.7% (n=271)
 Ischaemic heart disease reduces blood supply to the heart muscles and is one of the major cardiovascular diseases.
Chapter 14 Patterns in Health and Disease: Epidemiology and Physiology EXERCISE PHYSIOLOGY Theory and Application to Fitness and Performance, 6th edition.
Cardiovascular Disease Prevention Know, Understand, and Act University of Ottawa Heart Institute Division of Prevention & Rehabilitation.
Taking a life-course perspective – does previous drinking matter? Annie Britton Research Department of Epidemiology and Public Health University College.
Statistics Canada National Population Health Surveys (NPHS) Amir Erfani, PhD. Department of Sociology Nipissing University North Bay,
Cancer Risk Factors in Ontario Alcohol. Proportion of cancer cases attributable to alcohol consumption, by sex and cancer type, Ontario, Cancer.
ALCOHOL BY: NIBEN PADRIQUE. ATTENTION ACCORDING TO THE FOUNDATION FOR A DRUG FREE WORLD, IN 2005, 6.6% OF THE US POPULATION AGED 12 OR OLDER, OR 16 MILLION.
RISK FACTORS – CVD.
An Example of Working with Data Documentation
Presentation transcript:

STAR Webinar - December 20th, 2012 Stroke POpulation Risk Tool

STAR Webinar - December 20th, 2012 What is a Stroke?

STAR Webinar - December 20th, 2012

Effects of a Stroke

STAR Webinar - December 20th, 2012 Stroke Prediction Models FraminghamUSA ScoreAustralian Interstroke22 Countries QriskEngland-Wales 1993 – 2008 SPoRTCanada

STAR Webinar - December 20th, 2012 Development Cohort CCHS 1.132,848Sep 2000/Nov 2001 CCHS ,679Jan 2003 / Jan 2004 CCHS 3.133,402Jan 2005 / Jan 2006 Linked to Ontario health administration data until March 31, Registered Person Database CIHI/DAD

STAR Webinar - December 20th, 2012 Development Cohort (CCHS 1.1 – CCHS 3.1)

STAR Webinar - December 20th, 2012 Restrictions Risk factors available in public use files Excluding intermediate (ex. BMI) risk factors

STAR Webinar - December 20th, 2012 Competing Risk The type of failure that prevents the observation or fundamentally alters the probability of the occurrence of the event of interest. Death is a competing risk for stroke

Outcome Diagnostic codes for stroke were taken from Canadian Stroke Network Time to stroke STAR Webinar - December 20th, 2012

Variables STAR Webinar - December 20th, 2012 Age Smoking Alcohol Stress Physical activity Diet Education High blood pressure Diabetes

Risk Factor Categories Risk BehaviourCategoryDefinition SmokingHeavy smokerDaily current smoker (1 pack/day) Light smokerDaily current smoker (<1 pack/day) Former smokerFormer daily smoker Non-smokerFormer occasional smoker or never smoker AlcoholHeavy drinker >24 (men) or >17 (women) drinks/week in previous month or at least one binging in a week Moderate drinker5 to 24 (men) or 3 to 17 (women) drinks/week Light drinker0 to 4 (men) or 0 to 2 (women) drinks/week Occasional drinker<1 drink/month Current non-drinkerNo alcohol consumption in the last 12 months Physical activityInactive0 to <1.5 METs/day Moderately active1.5 to <3 METs/day Active3 METs/day DietPoor dietWeekly vegetable serving <7 Fair diet7 <= Weekly vegetable serving <14 Adequate diet14 <= Weekly vegetable serving Stress Very high stressSelf-perceived stress: quite a bit or extremely Somewhat stressSelf-perceived stress: a bit Low stressSelf-perceived stress: not at all or not very STAR Webinar - December 20th, 2012

Univariate Analysis Risk Factors and CategoriesMaleFemale SmokingHR (95% CI) Heavy 1.55 (1.17,2.04)2.20 (1.71,2.84) Light 1.41(1.07,1.84)1.67 (1.36,2.05) Former 1.16 (0.98,1.41)1.02 (0.87,1.2) Non-smokerRef. Alcohol Heavy drinker 1.25 (0.93,1.70)1.12 (0.59,2.13) Moderate drinkerRef. Light drinker 0.99 (0.81,1.21)1.10 (0.88,1.38) Occasional drinker 1.09 (0.84,1.44)1.20 (0.95, 1.52) Current non-drinker 1.18 (0.95,1.47) 1.43 (1.16,1.76) Physical activity Inactive 1.28 (1.05,1.56)1.25 (1.02,1.54) Moderately active 1.21 (0.96,1.51)1.04 (0.82,1.32) ActiveRef. Diet Poor 1.54 (1.25,1.90)1.43 (1.18,1.73) Fair 1.25 (1.03,1.52)1.25 (1.06,1.46) AdequateRef. Stress Very high 1.22 (0.98,1.52)1.40 (1.16,1.69) Somewhat 1.06 (0.90,1.26)1.04 (0.90,1.22) LowRef.

STAR Webinar - December 20th, 2012 The Index Risk Factors and CategoriesMaleFemale SmokingHR (95% CI) Index Score HR (95% CI) Index Score Heavy 1.55 (1.17,2.04) (1.71,2.84) 4 Light 1.41(1.07,1.84) (1.36,2.05) 3 Former 1.16 (0.98,1.41) (0.87,1.2) 1 Non-smokerRef.0 0 Alcohol Heavy drinker 1.25 (0.93,1.70) (0.59,2.13) 2 Moderate drinkerRef.0 0 Light drinker 0.99 (0.81,1.21) (0.88,1.38) 1 Occasional drinker 1.09 (0.84,1.44) (0.95, 1.52) 1 Current non-drinker 1.18 (0.95,1.47) (1.16,1.76) 2 Physical activity Inactive 1.28 (1.05,1.56) (1.02,1.54) 1 Moderately active 1.21 (0.96,1.51) (0.82,1.32) 0 ActiveRef.0 0 Diet Poor 1.54 (1.25,1.90) (1.18,1.73) 2 Fair 1.25 (1.03,1.52) (1.06,1.46) 1 AdequateRef.0 0 Stress Very high 1.22 (0.98,1.52) (1.16,1.69) 2 Somewhat 1.06 (0.90,1.26) (0.90,1.22) 0 LowRef.0 0

Models STAR Webinar - December 20th, 2012 MaleFemale Risk Behavior Index (1.080,1.193)1.175 (1.129,1.222) Age 1.113(1.095,1.131)1.107 (1.090,1.125) Age spline (0.939,0.986) Age time varying ( , ) ( , ) Family Education More than Secondary School Ref. Secondary school or less (1.064,1.588)1.286 (1.077,1.536) Missing (0.757,1.905)0.724 (0.384,1.364) High Blood pressure No Ref. Yes (1.074,1.553)1.527 (1.285,1.814) Missing (0.133,7.154)2.251 (0.387,13.106) Diabetes No Ref. Yes (1.119,1.753)1.773 (1.439,2.184)

Model Assessment MaleFemale C-stat (95% CI)0.85 (0.83 – 0.86)0.87 (0.85 – 0.88) 75/ / # O-P > 20% 5/53 3/51 STAR Webinar - December 20th, 2012

Development Cohort (CCHS 4.1) FemaleMaleOverall Records Years follow up # strokes in overall follow-up

Development Cohort OverallMaleFemale n=82259n=37483n=44776 MeanSEMeanSEMeanSE Age Gender Male Female STAR Webinar - December 20th, 2012

Validation cohort OverallMaleFemale n= 28605n=13032n=15573 MeanSEMeanSEMeanSE Age Gender Male Female STAR Webinar - December 20th, 2012

Diagnostic codes Diagnostic codes for stroke were taken from Canadian Stroke Network definition as 362, 3623, 430, 431, 435, 436 for ICD-9 and G45, H340, H34.1, I60, I61, I63, I64 excluding I608, I636, and G454 for ICD-10.

STAR Webinar - December 20th, 2012 References: Lets talk about stroke. Heart & Stroke foundation Béland Y. Canadian Community Health Survey. Methodological overview. Health Reports, Vol. 13, No. 3, March 2002 OHIP Eligibility, Ontario Ministry of Health and Long Term Care Ref Type: Online source Pintilie M. Dealing with competing risks: testing covariates and calculating sample size. Stat Med 2002; 21 :

Melberg T, Nyg+Ñrd OK, Kuiper KK-J, Nordrehoug JE. Competing risk analysis of events 10 years after revascularization. Scand Cardiovasc J 2010; 44; Walter, Kremers, Concordance for survival time data: Fixed and time-dependent covariates and possible ties in predictor and time. Technical report series #80. April Claudia SanMartin STAR Webinar - December 20th, 2012 References:

Statistical evaluation of prognostic versus diagnostic models: Beyond the ROC curve Tripepi, G., Statistical methods for the assessment of prognostic biomarkers (part II); calibration and reclassification. Nephrol. Dial. Transplant 2010 May 25 (5): Epub 2010 Feb 18 Handbook of constructing composite indicators, OECD cysurveys/ pdf STAR Webinar - December 20th, 2012 References: