Quantitative health impact assessment in Copenhagen

Transcription

1 Quantitative health impact assessment in Copenhagen - an application of the DYNAMO-HIA model Astrid Ledgaard Holm Henrik Brønnum-Hansen University of Copenhagen Department of Public Health Section of Social Medicine

2 Aims of the project 1) Quantitatively assess future health effects of preventive interventions in Copenhagen 2) Apply the Dynamo-HIA model to the population of Copenhagen Dias 2

3 Quantitative health impact assessment and DYNAMO-HIA (1) Dynamo-HIA - Generic software tool for quantification in health impact assessment - Dynamic, multi-state simulation - Markov-based modelling approach Modelling of potential health effects in Dynamo-HIA - Simulate potential effects of intervention scenarios - Compare effects to reference scenario - Scenarios can be defined by changed risk factor exposure as regards prevalence and/or transition probabilities Policy or intervention Risk factor exposure RR Incidence/prevalence of disease and mortality Dias 3

4 Quantitative health impact assessment and DYNAMO-HIA (2) Input data - Risk factor exposure prevalence - Demographic data (population size, mortality and fertility) - Incidence and prevalence of relevant diseases - Mortality from relevant disease and all-cause mortality - Transition probabilities - Relative risks Outputs (in the future) - Risk factor exposure prevalence - Incidence and prevalence of relevant diseases - Mortality and survival - Life expectancy (with and without disease) Dias 4

5 DYNAMO-HIA model for Copenhagen - Background International level National level Local level Copenhagen (population: 550,000) Health impact assessment model for local planning Data for the population of Copenhagen Dias 5

6 DYNAMO-HIA model for Copenhagen - Data Data sources - Risk factor exposure prevalence - Danish National Health Survey - Population demographics - Statistics Denmark - Incidence and prevalence of relevant diseases - The Danish National Patient Register - Mortality from relevant diseases and all-cause - The Danish Register of Causes of Death - Estimates of relative risk - Epidemiological studies Dias 6

7 DYNAMO-HIA model for Copenhagen Methods (1) Large degree of immigration and emigration in and out of Copenhagen Population projections for Copenhagen Population projections for Denmark Males 2012 Males 2025 Males 2040 Females 2012 Females 2025 Females 2040 Health effects = age specific prevalence x population projections Dias 7

8 DYNAMO-HIA model for Copenhagen Methods (2) Net transitions - Net shifts between risk factor categories for each age group - Based on baseline age-specific prevalence of risk factor exposure - Minimum transitions needed to keep age-specific prevalence unchanged - Depends on ordering of risk factor categories Risk of logically impossible transitions (e.g. from current to never smoker) Modified transition probabilities for smoking Dias 8

9 DYNAMO-HIA model for Copenhagen 3 risk factors and 3 intervention scenarios Physical activity Risk factor categories - Sedentary - Light activity - Vigorous activity Intervention scenario - Shift from sedentary to light activity - Modelled by changed prevalence Dias 9

10 DYNAMO-HIA model for Copenhagen Scenarios (2) Alcohol Risk factor categories - < 250mg/day - 250mg/day 20g/day - 20g/day 40g/day - 40g/day 60g/day - > 60g/day Intervention scenario - All drink below the recommended intake of alcohol - Modelled by changed prevalence Dias 10

11 DYNAMO-HIA model for Copenhagen Scenarios (3) Smoking Risk factor categories - Never smoker - Current smoker - Former smoker Intervention scenario - Reduction to 4% smoking prevalence by % decrease in smoking initiation rate and 50% increase in (successful) quit rate - Change in transition probabilities Dias 11

12 DYNAMO-HIA model for Copenhagen Results (1) Risk factor prevalence in 2040 physical activity Sedentary Light physical activity Male Female Dias 12

13 DYNAMO-HIA model for Copenhagen Results (2) Risk factor prevalence in alcohol Low alcohol (20-40g/day for males and 250mg-20g/dag for females) High alcohol (40-60g/day for males and 20-40g/day for females) Male Female Dias 13

14 DYNAMO-HIA model for Copenhagen Results (3) Risk factor prevalence in smoking Never smoker Current smoker Former smoker Male Female Dias 14

15 DYNAMO-HIA model for Copenhagen Results (4) Disease prevalence 3.50% Prevalence of selected diseases in % 2.50% 2.00% 1.50% 1.00% Reference Physical activity Alcohol Smoking 0.50% 0.00% IHD Stroke IHD Stroke Males Females Dias 15

16 DYNAMO-HIA model for Copenhagen Results (5) Life expectancy Gain in life expectancy (years) Female Physical activity Alcohol Smoking Male Dias 16

17 Thank you for your attention! Questions? Dias 17