Marc Luy - Vienna Institute of Demography
The Impact of Smoking and Other Non-biological Factors on Sex Differences in Life Expectancy: An Analysis of 53 Developed Populations
Date: 03/20/2014 (Thu)
Time: 3:30pm- 5:00pm
Location: Seminar will be held on-site: Gross Hall - 270
Organizer: Ken Land
Meeting Schedule: Login or email the organizer to schedule a meeting.
All meetings will be held in the same location as the seminar unless otherwise noted.
8:30am - Breakfast
9:30am - OPEN
10:00am - OPEN
10:30am - OPEN
11:00am - Students - Bryce Bartlett
11:30am - Joseph Lariscy
12:00pm - OPEN
12:30pm - OPEN
1:15pm - join students' T32 Luncheon Presentation
2:45pm - Elizabeth Frankenberg
3:15pm - Prepare for seminar
3:30pm - Seminar Presentation (3:30pm to 5:00pm)
6:00pm - Dinner - Ken Land, Anatoli Yashin
Additional Comments:
ABSTRACT: Background: Tobacco consumption is seen as the predominant driver of both the trend and the extent of sex differences in life expectancy. We compare the impact of smoking to the effect of other non-biological factors to assess its significance among the causes that can be influenced by direct or indirect interference.
Methods: Sex differences in life expectancy are decomposed into fractions caused by biological factors, smoking, and other non-biological factors for 53 industrialized countries and the period 1955-2009. The biologically caused difference is assessed on the basis of mortality data for female and male members of Catholic orders. Smoking-attributable mortality is estimated by the Peto-Lopez method. The impact of other non-biological factors is derived from the difference between the estimates for the other two components and the overall sex difference in life expectancy.
Findings: The trend of the sex gap can indeed be attributed to smoking in most populations of the western world. However, with regard to the overall extent of male excess mortality, smoking is the main driver only in a minority of the studied populations. While the impact of smoking to the sex gap declines in all studied populations, the contribution of other non-biological factors is in most cases higher at the end than at the beginning of the observation period.
Conclusion: Over-generalised statements which might suggest that smoking is the main force behind the sex gap in all populations could be misleading. The public health sector rather needs population-specific estimates to introduce the most appropriate measures in order to further reduce the inequalities in life years between women and men. The results of this study demonstrate that, regardless of the prevailing effect of smoking, many populations have still remarkable potentials to further narrow their sex gaps in life expectancy.