Sleep medicine · 2026
Differential 11-year mortality risk among subgroups of excessive daytime sleepiness in community-dwelling older adults: The Yilan study, Taiwan.
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Lin Ying-Cen, Hsu Nai-Wei, Lin Ching-Heng, Tsao Hsuan-Ming, Huang Ling-Yun, Chou Pesus, Chen Hsi-Chung
Аннотация
OBJECTIVES: Excessive daytime sleepiness (EDS) is prevalent among older adults, yet its varied manifestations and etiologies often lead to equivocal clinical significance. This study aimed to identify phenotypic subtypes of EDS and examine whether these subtypes carry differential risks for mortality.
METHODS: This longitudinal, community-based, fixed-cohort study followed participants aged 65 and older. EDS was defined as a score of ≥ 11 on the Epworth Sleepiness Scale (ESS). K-means clustering analysis with 8 items of the ESS as indicator variables was performed to determine various classes of EDS. Sociodemographic and clinical characteristics were compared among subgroups. Meanwhile, Cox proportional hazards models were used to evaluate the between-group difference regarding 11-year all-cause mortality risk.
RESULTS: A total of 3973 older adults participated, with an average follow-up period of 7.9 ± 3.0 years, and 16.0% of ESS ≥ 11. K-means clustering analysis yielded 3 EDS subgroups. Four phenotypic subgroups were designated as normal (ESS <11, 84.0%), high ESS (2.8%), mild ESS (5.3%), and low-active ESS (7.9%), with mild ESS group scored lowest in ESS. After controlling for various covariates, only participants in mild ESS group had higher mortality risk (HR: 1.59; 95% CI: 1.07-2.36), when compared with those in normal group.
CONCLUSIONS: In older adults, EDS comprises heterogeneous phenotypes associated with varying mortality risks. Our findings suggest that the specific symptom profile, rather than aggregate symptom severity, may hold greater clinical implications for the evaluation and management of EDS in older adults.
METHODS: This longitudinal, community-based, fixed-cohort study followed participants aged 65 and older. EDS was defined as a score of ≥ 11 on the Epworth Sleepiness Scale (ESS). K-means clustering analysis with 8 items of the ESS as indicator variables was performed to determine various classes of EDS. Sociodemographic and clinical characteristics were compared among subgroups. Meanwhile, Cox proportional hazards models were used to evaluate the between-group difference regarding 11-year all-cause mortality risk.
RESULTS: A total of 3973 older adults participated, with an average follow-up period of 7.9 ± 3.0 years, and 16.0% of ESS ≥ 11. K-means clustering analysis yielded 3 EDS subgroups. Four phenotypic subgroups were designated as normal (ESS <11, 84.0%), high ESS (2.8%), mild ESS (5.3%), and low-active ESS (7.9%), with mild ESS group scored lowest in ESS. After controlling for various covariates, only participants in mild ESS group had higher mortality risk (HR: 1.59; 95% CI: 1.07-2.36), when compared with those in normal group.
CONCLUSIONS: In older adults, EDS comprises heterogeneous phenotypes associated with varying mortality risks. Our findings suggest that the specific symptom profile, rather than aggregate symptom severity, may hold greater clinical implications for the evaluation and management of EDS in older adults.