| 英文摘要 |
Objectives: To describe period and birth-cohort patterns in self-reported multimorbidity in middle-aged and older Taiwanese adults during the early consolidation of Taiwan’s National Health Insurance, distinguish changes in institutional visibility from differences in health across birth cohorts, and clarify which findings can and cannot be identified from age-period-cohort analysis. Methods: Four pooled waves of the Taiwan Longitudinal Study on Aging (1993–2003) included 18,049 person-wave observations from 7,397 respondents. Multimorbidity was defined as two or more of eight self-reported physician-diagnosed conditions. Severity-graded outcomes also incorporated activity limitations associated with these conditions. Conditional age-period-cohort logistic regression was performed, and confidence intervals (CIs) were estimated using 500 person-level cluster bootstrap replicates. Partial identification was performed by fixing the linear age slope at different values along the solution line. Attrition was examined using inverse-probability weighting and extreme-value bounds. The 2011 wave (n = 3,727) was analyzed as an extension. Results: Age-standardized prevalence over the common age≥65-year support increased from 33.8% in 1993 to 43.9% in 2003 and 47.9% in 2011. The period component reached a nadir in 1996 (odds ratio [OR] = 0.78, 95% CI [0.73, 0.83]) and increased to 1.36 [1.16, 1.57] in 2003. The cohort component plateaued for the 1920–1929 birth cohorts (OR, approximately 1.44) and declined to 0.46 [0.25, 0.90] for 1950–1954 birth cohort. Constraint-free nonlinear estimates confirmed a nadir in 1996 (OR = 0.85 [0.82, 0.89]) and a peak for the 1925–1929 birth cohort (OR = 1.37 [1.19, 1.55]). However, the magnitude of the linear trends depended on the assumed age slope. The period-related increase was smaller for the severity-graded outcome (2003, OR = 1.17 vs 1.36). Conclusions: The observed multimorbidity trajectory is compatible with both period-related and birth-cohort interpretations. Chronic disease monitoring should report period and cohort components separately and distinguish quantities that are identified from those that depend on model assumptions. |