Stewart, Cutler, and Rosen 2009 — Forecasting the Effects of Obesity and Smoking on U.S. Life Expectancy

life-expectancyobesitysmokingbehavioral-risk-factorsQALEquality-adjusted-life-expectancyforecastingNHANESMEPSCox-proportional-hazardslife-tabledemographypublic-healthmortalityNBER

Summary

Stewart, Cutler, and Rosen use life-table simulation to forecast 2005–2020 U.S. life expectancy (LE) and quality-adjusted life expectancy (QALE) for a representative 18-year-old, given simultaneous trends in rising body mass index (BMI, +0.5%/year) and declining smoking (−1.4%/year). The BMI increase (−1.02 LE years) overwhelms the smoking benefit (+0.31 LE years), producing a net combined effect of −0.71 LE years and −0.91 QALE years over the forecast window. The paper validates the model against 1990–2004 historical trends (actual gain: 2.44 years vs. 2.98-year no-change counterfactual) and shows that full elimination of both risk factors would yield +3.76 LE years and +5.16 QALE years.

Key Claims

Concepts Introduced or Extended

Entities Mentioned

Quotes

"Unless effective strategies to reduce obesity are developed, the negative effect of obesity on life expectancy will increasingly offset the positive effect of declining smoking rates."

"We project that if recent trends in the prevalence of obesity and smoking continue, they will have a combined effect of reducing life expectancy by 0.71 years by 2020."

My Take

The paper's central contribution is methodological transparency: by decomposing smoking and BMI effects separately before combining them, it demonstrates that the obesity drag is approximately 3× larger than the smoking benefit — making the net direction of LE change in the medium term a function of which trend dominates. The threshold finding (0.15%/year BMI growth) is particularly policy-relevant: it shows there is essentially no "slow-growth" scenario under which obesity has a neutral effect unless BMI growth actually stops. The historical validation (1990–2004) is credible, though the counterfactual implicitly assumes no other risk-factor changes. The paper does not model race/socioeconomic-status (SES) heterogeneity, meaning the forecasted LE drag is likely worse for lower-SES groups where obesity rates are rising fastest. Also directly relevant to SSA Mortality Forecasting: this paper's framework demonstrates why LE projections ignoring obesity and smoking covariates (as the Social Security Administration's (SSA) Office of the Chief Actuary (OACT) historically did) are systematically overoptimistic.