Work in Progress Simulating the Local Dynamics of Cardiovascular Health and Related Risk Factors Jack Homer Homer Consulting [email protected]Bobby Milstein Centers for Disease Control and Prevention [email protected]University of Michigan Tobacco Modeling Meeting May 2008 This work was funded by the CDC’s Division for Heart Disease and Stroke Prevention and by the National Institutes of Health’s Office of Behavioral and Social Science Research. The work was done in collaboration with the Health and Human Services Department of Austin/Travis County, Texas, and with Indigent Care Collaboration of Central Texas. The external contractors are Sustainability Institute and RTI International.
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Work in Progress Simulating the Local Dynamics of Cardiovascular Health and Related Risk Factors
Work in Progress Simulating the Local Dynamics of Cardiovascular Health and Related Risk Factors. Jack Homer Homer Consulting [email protected] Bobby Milstein Centers for Disease Control and Prevention [email protected] University of Michigan Tobacco Modeling Meeting May 2008. - PowerPoint PPT Presentation
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Work in Progress
Simulating the Local Dynamics of Cardiovascular Health and
University of Michigan Tobacco Modeling MeetingMay 2008
This work was funded by the CDC’s Division for Heart Disease and Stroke Prevention and by the National Institutes of Health’s Office of Behavioral and Social Science Research. The
work was done in collaboration with the Health and Human Services Department of Austin/Travis County, Texas, and with Indigent Care Collaboration of Central Texas. The
external contractors are Sustainability Institute and RTI International.
ContributorsCore Design Team• CDC: Darwin Labarthe, Diane Orenstein, Bobby Milstein, Marilyn
Metzler, Rosanne Farris• Austin: Adolfo Valadez, Phil Huang, Karina Loyo, Rick
Schwertfeger, Cindy Batcher, Ella Pugo, Josh Vest • NIH: Patty Mabry• Consultants: Kristina Wile, Jack Homer, Justin Trogdon
Organizational Sponsors• Austin/Travis County Health and Human Services Department• CDC Division for Heart Disease and Stroke Prevention• CDC Division of Adult and Community Health• CDC Division of Nutrition, Physical Activity, and Obesity• CDC Division of Diabetes Translation • CDC Office on Smoking and Health• CDC NCCDPHP Office of the Director• Indigent Care Collaborative (Austin, TX)• NIH Office of Behavioral and Social Science Research• RTI International• Sustainability Institute• Texas Department of Health
• How do local conditions affect multiple risk factors for CVD, and how do those risks, in turn, affect population health status and costs over time?
• How do different local interventions affect cardiovascular health and related expenditures in the short- and long-term?
• How might local health leaders better balance their policy efforts given limited resources?
Smoking
Obesity
Secondhandsmoke
Healthinessof diet
Extent ofphysical activity
Psychosocialstress
Diagnosisand control
First-time CVevents and
deaths
Access to and marketingof smoking quit products
and services
Access to andmarketing of mental
health services
Sources ofstress
Access to andmarketing of healthy
food options
Access to andmarketing of physical
activity options
Access to andmarketing of weight
loss services
Access to andmarketing ofprimary care
Particulate airpollution
Utilization ofquality primary
care
Tobacco taxes andsales/marketing
regulations
Smoking bans atwork and public
places
Junk food taxes andsales/marketing
regulations
Downwardtrend in CV
event fatality
Quality of primarycare provision
Chronic Disorders
Costs from CV and other riskfactor complications and
from utilization of services
Anti-smokingsocial marketing
High BP
Highcholesterol
Diabetes
The CDC is partnering on this project with the Austin (Travis County), Texas, Dept. of Health and Human Services. The model is calibrated to represent the
overall US, but is informed by the experience and data of the Austin team, which has been supported by the CDC’s “STEPS” program since 2004.
The CDC is partnering on this project with the Austin (Travis County), Texas, Dept. of Health and Human Services. The model is calibrated to represent the
overall US, but is informed by the experience and data of the Austin team, which has been supported by the CDC’s “STEPS” program since 2004.
Homer J, Milstein B, Wile K, Pratibhu P, Farris R, Orenstein D. Modeling the local dynamics of cardiovascular health: risk factors, context, and capacity. Preventing Chronic Disease 2008;5(2). Available at http://www.cdc.gov/pcd/issues/2008/apr/07_0230.htm
Based on well-established Framingham approach for calculating probability of first-time events & deaths in individuals• CVD = CHD (MI, angina, cardiac arrest) + Stroke/TIA + CHF + PAD
Modifies individual-level risk calculator for use with populations• Uses prevalences of uncontrolled chronic disorders by sex/age group
• Introduces secondhand smoke and pollution as additional risk factors
• Combines risks multiplicatively to account for overlapping conditions
• Adjustment exponents reproduce synergies seen in individual-level calculator
• Adjustment multipliers reproduce AHA event and death frequencies for 2003
- Anderson et al, Am Heart J 1991 (based on Framingham MA population N=5573, 1968-1987)
- Homer “Risk calculation in the CVD model” project document, June 19, 2007
- NHANES 1988-94 & 1999-04
- AHA Heart Disease and Stroke Statistics – 2006 Update
• Census– Population, deaths, births, net immigration, health coverage
• AHA & NIH statistical reports – Cardiovascular events, deaths, and prevalence (CHD, stroke, CHF, PAD)
• National Health and Nutrition Examination Survey (NHANES) – Risk factor prevalences by age (18-29, 30-64, 65+) and sex (M, F)– Chronic disorder diagnosis and control (hypertension, high cholesterol, diabetes)
• Behavioral Risk Factor Surveillance System (BRFSS)– Diet & physical activity– Primary care utilization– Lack of needed emotional/social support Psychosocial stress
• Medical Examination Panel (MEPS) / National Health Interview (NHIS) – Medical and productivity costs attributable to smoking, obesity, and chronic disorders
• Research literature– CVD risk calculator, and relative risks from SHS, air pollution, obesity, and inactivity– Medical and productivity costs of cardiovascular events
• Questionnaires for CDC and Austin teams (expert judgment)– Potential effects of social & services marketing on utilization behavior– Effects of behavioral services on smoking, weight loss, stress reduction– Relative risks of stress for high BP, high cholesterol, smoking, and obesity
Baseline If Full Access If Full Access,Max Mktg & Max
Quality Care
% o
f s
mo
ke
rs u
sin
g q
uit
sv
cs
Use of Quit Services by Smokers
Sources: - MEPS spending analysis, re: baseline use of quit services and products- Terry Pechacek CDC, personal correspondence, citing Group Health Cooperative study, re: effects of marketing and quality primary care
In the base run, the fraction of non-smokers with significant secondhand smoke exposure declines from 19.1% in 2010 to 15.4% in 2040, tracking the decline in smoking. The AirQ2 intervention cluster reduces the 2040 value to 4.2% (due to the effect of indoor smoking
laws), and then adding the Tob4 cluster reduces it to 1.5%.
Effects of Interventions on Preventable Deaths (2010-2040 cumulative)
Cumulative deaths 2010-2040 (in non-CVD population) from CV and other risk factor complications, in millions
From From Other CV Complications CombinedBase 19.6 10.8 30.4PC3 17.7 10.4 28.2PC3AirQ2 17.1 10.3 27.4PC3AirQ2Tob4 16.6 6.8 23.5All19 16.1 6.5 22.6
Over 30 years, the “Tob4” intervention cluster reduces CV deaths by 0.5m, and reduces other deaths (cancers & respiratory) by 3.4m, for a total reduction of 3.9m. Note that the CV deaths are based on the Framingham methodology, whereas the smoking-related deaths from other complications are based on
• Historical estimates of current smoking prevalence among non-CVD popn from NHANES 1988-94 and 1999-2004 by sex and age group.
• Smoking prevalence in adults is modeled as a stock affected by flows of initiation and quitting, by the inflow of teen smokers turning age 18, and by deaths (related to CVD and otherwise).
• Historical estimates of Age 18 smoking fraction by sex from YRBSS.
• Baseline rates of adults quitting smoking based on Mendez & Warner AJPH 2007 and Sloan et al MIT Press 2004 (Fig. 2.1)
• Baseline rates of adult initiation/relapse adjusted to reproduce NHANES adult smoking trends by sex and age.
• Historical estimates of current smoking prevalence among non-CVD popn from NHANES 1988-94 and 1999-2004 by sex and age group.
• Smoking prevalence in adults is modeled as a stock affected by flows of initiation and quitting, by the inflow of teen smokers turning age 18, and by deaths (related to CVD and otherwise).
• Historical estimates of Age 18 smoking fraction by sex from YRBSS.
• Baseline rates of adults quitting smoking based on Mendez & Warner AJPH 2007 and Sloan et al MIT Press 2004 (Fig. 2.1)
• Baseline rates of adult initiation/relapse adjusted to reproduce NHANES adult smoking trends by sex and age.
Simulating the Local Dynamics of Cardiovascular Health and Related Risk Factors
Homer J, Milstein B, Wile K, Pratibhu P, Farris R, Orenstein D. Modeling the local dynamics of cardiovascular health: risk factors, context, and capacity. Preventing Chronic Disease 2008;5(2). Available at http://www.cdc.gov/pcd/issues/2008/apr/07_0230.htm