A discrete latent factor model of smoking, cancer and mortality

TY - JOUR

T1 - A discrete latent factor model of smoking, cancer and mortality

AU - Howdon, Daniel

AU - Jones, Andrew M.

N1 - © Elsevier 2015. This is an author produced version of a paper published in Economics and Human Biology. Uploaded in accordance with the publisher's self-archiving policy.

PY - 2015/7

Y1 - 2015/7

N2 - This paper investigates the relationship between smoking and ill-health, with a focus on the onset of cancer. A discrete latent factor model for smoking and health outcomes, allowing for these to be commonly affected by unobserved factors, is jointly estimated, using the British Health and Lifestyle Survey (HALS) dataset. Post-estimation predictions suggest the reduction in time-to-cancer to be 5.7 years for those with an exposure of 30 pack-years, compared to never-smokers. Estimation of posterior probabilities for class membership shows that individuals in certain classes exhibit similar observables but highly divergent health outcomes, suggesting that unobserved factors influence outcomes. The use of a joint model changes the results substantially. The results show that failure to account for unobserved heterogeneity leads to differences in survival times between those with different smoking exposures to be overestimated by more than 50% (males, with 30 pack-years of exposure).

AB - This paper investigates the relationship between smoking and ill-health, with a focus on the onset of cancer. A discrete latent factor model for smoking and health outcomes, allowing for these to be commonly affected by unobserved factors, is jointly estimated, using the British Health and Lifestyle Survey (HALS) dataset. Post-estimation predictions suggest the reduction in time-to-cancer to be 5.7 years for those with an exposure of 30 pack-years, compared to never-smokers. Estimation of posterior probabilities for class membership shows that individuals in certain classes exhibit similar observables but highly divergent health outcomes, suggesting that unobserved factors influence outcomes. The use of a joint model changes the results substantially. The results show that failure to account for unobserved heterogeneity leads to differences in survival times between those with different smoking exposures to be overestimated by more than 50% (males, with 30 pack-years of exposure).

KW - Health inequality

KW - Duration analysis

KW - Smoking

KW - Cancer

U2 - 10.1016/j.ehb.2015.03.004

DO - 10.1016/j.ehb.2015.03.004

M3 - Article

SN - 1570-677X

VL - 18

SP - 57

EP - 73

JO - Economics and Human Biology

JF - Economics and Human Biology

ER -