Effects of population aging on quality of life and disease burden: a population-based study.

BACKGROUND

As population aging intensifies, it becomes increasingly important to elucidate the casual relationship between aging and changes in population health. Therefore, our study proposed to develop a systematic attribution framework to comprehensively evaluate the health impacts of population aging.

METHODS

We used health-adjusted life expectancy (HALE) to measure quality of life and disability-adjusted life years (DALY) to quantify the burden of disease for the population of Guangzhou. The HALE and DALY projections were generated using both the Bayesian age-period-cohort models and the population prediction models. Changes in HALE and DALY between 2010-2020 and 2020-2030 were decomposed to isolate the effects of population aging. Three scenarios were analyzed  to examine the relative relationship between disease burden and population aging. In Scenarios 1 and 2, the disease burden rates in 2030 were assumed to  either remain at 2020 levels or follow historical trends. In Scenario 3, it was assumed that the absolute numbers of years of life lost (YLL) and years lived with disability (YLD) in 2030 would remain unchanged from the 2020 levels.

RESULTS

Between 2010 and 2020, 56.24% [69.73%] of the increase in male [female, values in brackets] HALE was attributable to the mortality effects in the population aged 60 and over, while - 3.74% [- 9.29%] was attributable to the disability effects. The increase in DALY caused by changes in age structure accounted for 72.01% [46.68%] of the total increase in DALY. From 2020 to 2030, 61.43% [69.05%] of the increase in HALE is projected to result from the mortality effects in the population aged 60 and over, while - 3.88% [4.73%] will be attributable to the disability effects. The increase in DALY due to changes in age structure is expected to account for 102.93% [100.99%] of the total increase in DALY. In Scenario 1, YLL are projected to increase by 45.0% [54.7%], and YLD by 31.8% [33.8%], compared to 2020. In Scenario 2, YLL in 2030 is expected to decrease by - 2.9% [- 1.3%], while YLD will increase by 12.7% [14.7%] compared to 2020. In Scenario 3, the expected YLL rates and YLD rates in 2030 would need to be reduced by 15.3% [15.4%] and 15.4% [15.6%], respectively, compared to 2020.

CONCLUSIONS

The disability effects among the elderly population hinder improvements in quality of life, while changes in age structure are the primary driver of disease burden accumulation. To mitigate the excess disease burden caused by population aging, it is essential to achieve a reduction of more than 15% in the disease burden by 2030 compared to 2020. Our proposed attribution framework evaluates the health impacts of population aging across two dimensions: quality of life and disease burden. This framework enables comparisons of these effects over time and across different regions.