, Ji-Yeon Shin2
, Yu-Mi Lee2
, Duk-Hee Lee2
1Department of Epidemiology and Health Promotion, Graduate School of Public Health, Kyungpook National University, Daegu, Korea
2Department of Preventive Medicine, Kyungpook National University School of Medicine, Daegu, Korea
© 2026, Korean Society of Epidemiology
This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Conflict of interest
The authors have no conflicts of interest to declare for this study.
Funding
None.
Acknowledgements
None.
Author contributions
Conceptualization: Lee DH. Data curation: Kim G. Formal analysis: Kim G. Funding acquisition: None. Methodology: Lee DH. Visualization: Kim G. Writing – original draft: Kim G. Writing – review & editing: Shin JY, Lee YM, Lee DH.
| Gender | Year | Observed deaths | Expected deaths1 | P-score (95% CI)2 |
|---|---|---|---|---|
| All | 2020 | 7,510 | 7,235 | +3.8 (+1.5, +6.2) |
| 2021 | 7,249 | 6,869 | +5.5 (+3.1, +8.0) | |
| 2022 | 7,147 | 6,465 | +10.6 (+8.0, +13.1) | |
| 2023 | 7,229 | 5,989 | +20.7 (+17.9, +23.5) | |
| Men | 2020 | 4,955 | 4,851 | +2.2 (-0.7, +5.0) |
| 2021 | 4,807 | 4,634 | +3.7 (+0.8, +6.7) | |
| 2022 | 4,769 | 4,384 | +8.8 (+5.7, +11.9) | |
| 2023 | 4,620 | 4,080 | +13.2 (+10.0, +16.5) | |
| Women | 2020 | 2,703 | 2,500 | +8.1 (+4.0, +12.2) |
| 2021 | 2,480 | 2,357 | +5.2 (+1.1, +9.4) | |
| 2022 | 2,527 | 2,203 | +14.7 (+10.2, +19.2) | |
| 2023 | 2,484 | 2,025 | +22.7 (+17.8, +27.5) |
| Age (yr) | Year | Observed deaths | Expected deaths1 | P-score (95% CI)2 |
|---|---|---|---|---|
| 20–59 | 2020 | 1,573 | 1,518 | +3.7 (–1.5, +8.8) |
| 2021 | 1,365 | 1,401 | –2.7 (–7.9, +2.5) | |
| 2022 | 1,252 | 1,288 | –2.8 (–8.2, +2.6) | |
| 2023 | 1,211 | 1,176 | +3.0 (–2.8, +8.8) | |
| 60–79 | 2020 | 3,361 | 3,064 | +9.7 (+6.0, +13.4) |
| 2021 | 3,243 | 2,817 | +15.1 (+11.2, +19.1) | |
| 2022 | 3,333 | 2,514 | +32.6 (+28.1, +37.1) | |
| 2023 | 3,176 | 2,167 | +46.6 (+41.5, +51.7) | |
| ≥80 | 2020 | 2,576 | 2,629 | –2.0 (–5.8, +1.8) |
| 2021 | 2,641 | 2,610 | +1.2 (–2.7, +5.1) | |
| 2022 | 2,562 | 2,590 | –1.1 (–4.9, +2.8) | |
| 2023 | 2,841 | 2,519 | +12.8 (+8.6, +16.9) |
| Gender | Year | Observed deaths | Expected deaths |
P-score (95% CI) |
|---|---|---|---|---|
| All | 2020 | 7,510 | 7,235 | +3.8 (+1.5, +6.2) |
| 2021 | 7,249 | 6,869 | +5.5 (+3.1, +8.0) | |
| 2022 | 7,147 | 6,465 | +10.6 (+8.0, +13.1) | |
| 2023 | 7,229 | 5,989 | +20.7 (+17.9, +23.5) | |
| Men | 2020 | 4,955 | 4,851 | +2.2 (-0.7, +5.0) |
| 2021 | 4,807 | 4,634 | +3.7 (+0.8, +6.7) | |
| 2022 | 4,769 | 4,384 | +8.8 (+5.7, +11.9) | |
| 2023 | 4,620 | 4,080 | +13.2 (+10.0, +16.5) | |
| Women | 2020 | 2,703 | 2,500 | +8.1 (+4.0, +12.2) |
| 2021 | 2,480 | 2,357 | +5.2 (+1.1, +9.4) | |
| 2022 | 2,527 | 2,203 | +14.7 (+10.2, +19.2) | |
| 2023 | 2,484 | 2,025 | +22.7 (+17.8, +27.5) |
| Age (yr) | Year | Observed deaths | Expected deaths |
P-score (95% CI) |
|---|---|---|---|---|
| 20–59 | 2020 | 1,573 | 1,518 | +3.7 (–1.5, +8.8) |
| 2021 | 1,365 | 1,401 | –2.7 (–7.9, +2.5) | |
| 2022 | 1,252 | 1,288 | –2.8 (–8.2, +2.6) | |
| 2023 | 1,211 | 1,176 | +3.0 (–2.8, +8.8) | |
| 60–79 | 2020 | 3,361 | 3,064 | +9.7 (+6.0, +13.4) |
| 2021 | 3,243 | 2,817 | +15.1 (+11.2, +19.1) | |
| 2022 | 3,333 | 2,514 | +32.6 (+28.1, +37.1) | |
| 2023 | 3,176 | 2,167 | +46.6 (+41.5, +51.7) | |
| ≥80 | 2020 | 2,576 | 2,629 | –2.0 (–5.8, +1.8) |
| 2021 | 2,641 | 2,610 | +1.2 (–2.7, +5.1) | |
| 2022 | 2,562 | 2,590 | –1.1 (–4.9, +2.8) | |
| 2023 | 2,841 | 2,519 | +12.8 (+8.6, +16.9) |
CI, confidence interval. Expected deaths were estimated by applying linear regression to age-specific mortality trends from 2015 to 2019 and multiplying the predicted rates by the corresponding population counts for 2020 to 2023. P-scores (%) were calculated as (observed−expected)/expected×100.
CI, confidence interval. Expected deaths were estimated by applying linear regression to age-specific mortality trends from 2015 to 2019 and multiplying the predicted rates by the corresponding population counts for 2020 to 2023. P-scores (%) were calculated as (observed−expected)/expected×100.