Changes of the acute myocardial infarction-related resident deaths in a transitioning region: a real-world study involving 3.17 million people

Abstract

Background: The impact of acute myocardial infarction (AMI) on the life span of residents in a transitioning region has not been studied in depth. Therefore, we aimed to evaluate the changes in AMI-related resident deaths in a transitioning region in China.

Methods: A longitudinal, population-based study was performed to analyze the deaths with/of AMI in Pudong New Area (PNA), Shanghai from 2005 to 2021. The average annual percentage change (AAPC) of AMI in crude mortality rates (CMR), age-standardized mortality rates worldwide (ASMRW), and rates of years of life lost (YLLr) were calculated by the joinpoint regression. The impact of demographic and non-demographic factors on the mortality of residents who died with/of AMI was quantitatively analyzed by the decomposition method.

Results: In 7,353 residents who died with AMI, 91.74% (6,746) of them were died of AMI from 2005 to 2021. In this period, the CMR and ASMRW of residents died with/of AMI were 15.23/10⁵ and 5.17/10⁵ person-years, the AAPC of CMR was 0.01% (95% CI: -0.71,0.72, p = 0.989) and 0.06% (95% CI: -0.71,0.84, p = 0.868), and the ASMRW decreased by 2.83% (95% CI: -3.66,-2.00, p < 0.001) and 2.76% (95% CI: -3.56,-1.95, p < 0.001), respectively. The CMR of people died of AMI showed a downward trend (all p < 0.05) in people ≥60 years but an upward trend [AAPC = 2.47% (95% CI: 0.07,4.94, p = 0.045)] in people of 45-59 years. The change in CMR of people died with/of AMI caused by demographic factors was 28.70% (95% CI: 12.99,46.60, p = 0.001) and 28.07% (95% CI: 12.71,45.52, p = 0.001) per year, respectively.

Conclusion: Preventative strategies for AMI should be applied to enhance the health management of residents aged 45-59 years or with comorbidities in the transitioning region.

Keywords: acute myocardial infarction; comorbidities; mortality; trend analysis; years of life lost.

Figure 1

Flow chart for the selection of AMI-related deaths in PNA, Shanghai from 2005 to 2021.

Figure 2

Sequence map of causes of death by gender. (A) The top 10 underlying cause of death of residents died with AMI; (B) The top 10 comorbid diseases of residents died of AMI.

Figure 3

The trends in CMR, ASMRW, age specific proportions, and YLL of residents who died with/of AMI in genders and age groups in PNA, Shanghai, China, 2005–2021. (A) The trends in CMR, ASMRW, age specific proportions, and YLL of residents who died with AMI; (B) The trends in CMR, ASMRW, age specific proportions, and YLL of residents who died of AMI. CMR, crude mortality rate (per 100,000); ASMRW, age-standardized mortality rate by Segi’s world standard population (per 100,000); YLL, year of lost. AAPC, average annual percent change; CI, confidence interval.

Figure 4

Influences of demographic and non-demographic factors on AMI-related deaths during the period from 2005 to 2021 in PNA, Shanghai, China. (A1) The increased rates caused by demographic age structure in death with AMI; (A2) The increased rates caused by non-demographic age structure in death with AMI; (a1) The trend of the mortality rate caused by demographic age structure in death with AMI; (a2) The trend of the mortality rate caused by non-demographic age structure in death with AMI; (B1) The increased rates caused by demographic age structure in death of AMI; (B2) The increased rates caused by non-demographic age structure in death of AMI; (b1) The trend of the mortality rate caused by demographic age structure in death of AMI; (b2) The trend of the mortality rate caused by non-demographic age structure in death of AMI; AAPC, average annual percent change; CI, confidence interval.