Quantifying the contribution of changes in healthcare expenditures and smoking to the reversal of the trend in life expectancy in the Netherlands.

BACKGROUND: Since 2001 the Netherlands has shown a sharp upturn in life expectancy (LE) after a longer period of slower improvement. This study assessed whether changes in healthcare expenditure (HCE) explain this reversal in trends in LE. As an alternative explanation, the impact of changes in smoking behavior was also evaluated. METHODS: To quantify the contribution of changes in HCE to changes in LE, we estimated a health-production function using a dynamic panel regression approach with data on 19 OECD countries (1980-2009), accounting for temporal and spatial correlation. Smoking-attributable mortality was estimated using the indirect Peto-Lopez method. RESULTS: As compared to 1990-1999, during 2000-2009 LE in the Netherlands increased by 1.8 years in females and by 1.5 years in males. Whereas changes in the impact of smoking between the two periods made almost no contribution to the acceleration of the increase in LE, changes in the trend of HCE added 0.9 years to the LE increase between 2000 and 2009. The exceptional reversal in the trend of LE and HCE was not found among the other OECD countries. CONCLUSION: This study suggests that changes in Dutch HCE, and not in smoking, made an important contribution to the reversal of the trend in LE; these findings support the view that investments in healthcare are increasingly important for further progress in life expectancy.

The impact of smoking on gender differences in life expectancy: more heterogeneous than often stated.

BACKGROUND: Throughout industrialized countries, tobacco consumption is seen as the predominant driver of both the trend and the extent of gender differences in life expectancy. However, several factors raise doubts to this generalization. We hypothesize that the impact of smoking on the gender gap is context-specific and differs between populations. METHODS: We decompose the gender differences in life expectancy into fractions caused by smoking and other non-biological factors for 53 industrialized countries and the period 1955-2009 to assess the significance of smoking among the causes that can be influenced by direct or indirect interference. RESULTS: The trend of the gender 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 the minority of the studied populations. While the impact of smoking to gender differences in life expectancy declines in all populations, the contribution of other non-biological factors is in most cases higher at the end than at the beginning of the observation period. CONCLUSIONS: Over-generalized statements suggesting that smoking is the main driver of the gender gap in all populations can be misleading. The results of this study demonstrate that-regardless of the prevailing effect of smoking-many populations have still remarkable potentials to further narrow their gender gaps in life expectancy. Although measures to further reduce the prevalence of tobacco consumption must be continued, more attention should be directed to the growing importance of other non-biological factors.