TY - JOUR
T1 - Reevaluating the role of biological aging in dementia
T2 - a retrospective cross-sectional global analysis incorporating confounding factors
AU - You, Wenpeng
AU - Koo, Fung Kuen
AU - Ge, Yanfei
AU - Sevastidis, Jacob
AU - Chang, Rita (Hui Chen)
N1 - Publisher Copyright:
© 2025 The Author(s)
PY - 2025/5/1
Y1 - 2025/5/1
N2 - Background: Biological aging is a key dementia risk factor, but its precise role is debated. This study explores the impact of life expectancy at birth (LEB) on global dementia incidence rates (DIR). Methods: A retrospective cross-sectional analysis was conducted using population-level data from the World Bank and the Institute for Health Metrics and Evaluation (IHME). Pearson's r and nonparametric correlations assessed associations, while partial correlation analysis and multiple regression models were employed to adjust for confounders, including economic affluence, genetic predisposition (Ibs), total fertility rate, and urbanization. Results: LEB showed a strong initial correlation with DIR, explaining 58.05 % of the variance. However, after adjusting for confounders, the independent contribution of LEB to DIR was reduced to 5.95 %. Total fertility rate emerged as the most significant predictor, with LEB being the second strongest. Economic affluence, Ibs, and urbanization were not statistically significant. Conclusions: This study challenges the view that dementia is solely due to biological aging. While age remains crucial, biological aging accounts for less than 6 % of dementia incidence variance, highlighting the multifaceted nature of dementia risk factors.
AB - Background: Biological aging is a key dementia risk factor, but its precise role is debated. This study explores the impact of life expectancy at birth (LEB) on global dementia incidence rates (DIR). Methods: A retrospective cross-sectional analysis was conducted using population-level data from the World Bank and the Institute for Health Metrics and Evaluation (IHME). Pearson's r and nonparametric correlations assessed associations, while partial correlation analysis and multiple regression models were employed to adjust for confounders, including economic affluence, genetic predisposition (Ibs), total fertility rate, and urbanization. Results: LEB showed a strong initial correlation with DIR, explaining 58.05 % of the variance. However, after adjusting for confounders, the independent contribution of LEB to DIR was reduced to 5.95 %. Total fertility rate emerged as the most significant predictor, with LEB being the second strongest. Economic affluence, Ibs, and urbanization were not statistically significant. Conclusions: This study challenges the view that dementia is solely due to biological aging. While age remains crucial, biological aging accounts for less than 6 % of dementia incidence variance, highlighting the multifaceted nature of dementia risk factors.
UR - http://www.scopus.com/inward/record.url?scp=105004583371&partnerID=8YFLogxK
U2 - 10.1016/j.gerinurse.2025.04.023
DO - 10.1016/j.gerinurse.2025.04.023
M3 - Article
SN - 1528-3984
SN - 0197-4572
VL - 63
SP - 643
EP - 651
JO - Geriatric Nursing
JF - Geriatric Nursing
ER -