All-Cause and Cause-Specific Mortality Attributable to Seasonal Influenza: A Nationwide Matched Cohort Study
Journal of Korean Medical Science
; : e188-2023.
Article
in En
| WPRIM
| ID: wpr-1001145
Responsible library:
WPRO
ABSTRACT
Background@#Although influenza poses substantial mortality burden, most studies have estimated excess mortality using time-aggregated data. Here, we estimated mortality risk and population attributable fraction (PAF) attributed to seasonal influenza using individual-level data from a nationwide matched cohort. @*Methods@#Individuals with influenza during four consecutive influenza seasons (2013–2017) (n = 5,497,812) and 14 age- and sex-matched individuals without influenza (n = 20,990,683) were identified from a national health insurance database. The endpoint was mortality within 30 days after influenza diagnosis. All-cause and cause-specific mortality risk ratios (RRs) attributed to influenza were estimated. Excess mortality, mortality RR, and PAF of mortality were determined, including for underlying disease subgroups. @*Results@#Excess mortality rate, mortality RR, and PAF of all-cause mortality were 49.5 per 100,000, 4.03 (95% confidence interval [CI], 3.63–4.48), and 5.6% (95% CI, 4.5–6.7%). Cause-specific mortality RR (12.85; 95% CI, 9.40–17.55) and PAF (20.7%; 95% CI, 13.2– 27.0%) were highest for respiratory diseases. In subgroup analysis according to underlying disorders, PAF of all-cause mortality was 5.9% (95% CI, 0.6–10.7%) for liver disease, 5.8% (95% CI, 2.9–8.5%) for respiratory disease, and 3.8% (95% CI, 1.4–6.1%) for cancer. @*Conclusion@#Individuals with influenza had a 4-fold higher mortality risk than individuals without influenza. Preventing seasonal influenza may lead to 5.6% and 20.7% reductions in all-cause and respiratory mortality, respectively. Individuals with respiratory disease, liver disease, and cancer may benefit from prioritization when establishing influenza prevention strategies.
Full text:
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Database:
WPRIM
Language:
En
Journal:
Journal of Korean Medical Science
Year:
2023
Document type:
Article