A Method for Partitioning the Attributable Fraction of Multiple Time-Dependent Coexisting Risk Factors for an Adverse Health Outcome.

MORTALITY risk factors; RISK assessment; STATISTICS methodology; DATA analysis; AGE factors in disease; CONFIDENCE intervals; CAUSES of death; DEMENTIA; HEART failure; LONGITUDINAL method; OBSTRUCTIVE lung diseases; EVALUATION of medical care; PNEUMONIA; RESEARCH funding; TIME; TUMORS; DECISION making in clinical medicine; COMORBIDITY; LOGISTIC regression analysis; SECONDARY analysis; PREDICTIVE validity; DESCRIPTIVE statistics

Objectives. We decomposed the total effect of coexisting diseases on a timed occurrence of an adverse outcome into additive effects from individual diseases. Methods. In a cohort of older adults enrolled in the Precipitating Events Project in New Haven County, Connecticut, we assessed a longitudinal extension of the average attributable fraction method (LE-AAF) to estimate the additive and order-free contributions of multiple diseases to the timed occurrence of a health outcome, with right censoring, which may be useful when relationships among diseases are complex. We partitioned the contribution to death into additive LEAAFs for multiple diseases. Results. The onset of heart failure and acute episodes of pneumonia during follow-up contributed the most to death, with the overall LE-AAFs equal to 13.0% and 12.1%, respectively. The contribution of preexisting diseases decreased over the years, with a trend of increasing contribution from new onset of diseases. Conclusions. LE-AAF can be useful for determining the additive and order-free contribution of individual time-varying diseases to a time-to-event outcome. [ABSTRACT FROM AUTHOR]