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Projecting Future Mortality Using Information on Health Behaviors David M. Cutler, Edward L. Glaeser, and Allison B. Rosen.

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Presentation on theme: "Projecting Future Mortality Using Information on Health Behaviors David M. Cutler, Edward L. Glaeser, and Allison B. Rosen."— Presentation transcript:

1 Projecting Future Mortality Using Information on Health Behaviors David M. Cutler, Edward L. Glaeser, and Allison B. Rosen

2 Questions Is the US population healthier than in the past? Is the US population healthier than in the past? –Yes: Smoking has declined greatly –No: We are more obese –Yes: We treat disease better Will these trends continue? Will these trends continue?

3 Restrictions We focus on health behaviors. We focus on health behaviors. –Smoking –Drinking –Weight –Taking medications

4 Actual Causes of Death in the United States, 2004 Tobacco18% Tobacco18% Obesity15% Obesity15% Alcohol 4% Alcohol 4% Microbial agents 3% Microbial agents 3% Toxic agents 2% Toxic agents 2% MVAs 2% MVAs 2% Guns 1% Guns 1% Sexual behaviors 1% Sexual behaviors 1% Illicit use of drugs 1% Illicit use of drugs 1% Source: Mokdad et al., 2004.

5 Methodology 1. Relate risk factors to subsequent mortality –NHANES I data (1971-75) linked to subsequent mortality 2. Evaluate change in risk factors, 1971-75 vs. 1999-2002 3. Consider forecasts about risk factors in the future.

6 Data NHANES I (1971-75) and NHANES 1999-2002 NHANES I (1971-75) and NHANES 1999-2002 Population 25-74 and 55-74 Population 25-74 and 55-74 Demographics Demographics Self reported smoking, alcohol Self reported smoking, alcohol Physical measures of BP, cholesterol, BMI Physical measures of BP, cholesterol, BMI

7 Rough relationships Demographics Behaviors Risk: BP, Cholesterol Mortality weight smoking

8 Mortality Equation: 10 year mortality as a function of… Age/sex (10 year age x sex) Age/sex (10 year age x sex) Race (white/black/other) Race (white/black/other) Education (<HS, HS, Some College, College+) Education (<HS, HS, Some College, College+) Smoker (current/former/never) Smoker (current/former/never) BMI (low, normal, overweight, obese) BMI (low, normal, overweight, obese) Alcohol (heavy, light, never) Alcohol (heavy, light, never) Blood pressure (normal, pre-HTN, Stage 1, Stage 2) Blood pressure (normal, pre-HTN, Stage 1, Stage 2) Cholesterol (low, borderline, high) Cholesterol (low, borderline, high)

9 Summary Statistics: Education NHANES I NHANES 1999-2002

10 Summary Statistics: Smoking NHANES I NHANES 1999-2002

11 Summary Statistics: Drinking NHANES I NHANES 1999-2002

12 Summary Statistics: BMI NHANES I NHANES 1999-2002

13 Summary Statistics: Hypertension NHANES I NHANES 1999-2002

14 Summary Statistics: High Cholesterol NHANES I NHANES 1999-2002

15 Effect of Risk Factors on 10 Year Mortality Variable Odds Ratio Variable Race: Black 1.40* BMI: Underweight 2.41* Other Other.25 Overweight Overweight0.76* Educ: <HS 1.27* Obese Obese1.28 College College1.06 BP: Pre-HTN 0.90 Smoke: Current 2.13* Stage 1 Stage 11.13 Former Former1.23 Stage 2 Stage 21.54* Drink: Heavy 1.02 Chol: Borderline 1.03 Light Light0.77* High High1.15

16 Predicted 10 Year Mortality Risk Risk in: Ages 25-74 Ages 55-74 1971-759.8%25.7% 1999-028.421.7 Change-1.4[-14%]-3.9[-15%]

17 Percentage Point Change in Risk Due to…

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19 Forecasts Simulate 20 years from now Simulate 20 years from now Not totally clear what explains these behaviors. Not totally clear what explains these behaviors. –Smoking: Taxes (a bit); Beliefs; Peer effects –Obesity: Lower (time) price of food –Assume these are still playing out

20 Forecasts Smoking Smoking –Know ever smoking for many cohorts (guess for others) –Assume trend reduction in current smoking continues –Smoking rate falls from 25% to 15%

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22 Forecast Assumptions Drinking Drinking –Continued reduction in heavy and light drinking BMI BMI –Same change in BMI over past 20 years as previous 20 years –Increase of about 10 lbs.

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24 Implications of higher BMI: BP and Cholesterol Use 1959-62 NHANES to relate BP and cholesterol to obesity Use 1959-62 NHANES to relate BP and cholesterol to obesity –Essentially no treatment Predict BP and cholesterol 20 years hence Predict BP and cholesterol 20 years hence –Includes random error term Assume same share of people treated and same impact of treatment Assume same share of people treated and same impact of treatment –Draw BP and cholesterol from distribution among treated.

25 Control of Adverse Risk Factors, 1999-2000

26 Impact of Changes on Population Mortality Rate %age points Percent Percent Smoking forecast -0.7%-8% Drinking forecast 0.1%1% BMI forecast 1.4%17% - If everyone takes meds - If everyone takes meds1.0%12% - More effective meds / - More effective meds / greater adherence greater adherence0.2%2%

27 Impact of 10% reduction in mortality on expected age at death for people alive at age 1.2 years 1.1 years 0.9 years 0.5 years

28 Results Impact of continued increase in obesity could be enormous. Impact of continued increase in obesity could be enormous. Key is risk factor control Key is risk factor control –Get more people treated –Improve effectiveness of therapy – better drugs, and taken more regularly

29 Qualifications Impact on mortality is not necessarily the same as impact on disability Impact on mortality is not necessarily the same as impact on disability –Important for DI and Medicare/Medicaid forecasts


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