Related Experiment Video
Updated: Jun 1, 2025

Measurement of Lifespan in Drosophila melanogaster
Published on: January 7, 2013
Incomplete Ascertainment of Mortality in a Nationally Representative Longitudinal Study of Community-Living Older
Thomas M Gill1, Jingchen Liang2, Brent Vander Wyk1
1Yale School of Medicine, Department of Internal Medicine, New Haven, Connecticut, USA.
Background:
In longitudinal studies of older persons, complete ascertainment of mortality is needed to minimize potential biases. To ascertain mortality in the National Health and Aging Trends Study (NHATS), investigators most commonly use its Sensitive files, which include month and year of death on most decedents who had not dropped out of the study. Because losses to follow-up are not insubstantial, ascertainment of mortality is likely incomplete.
Methods:
We used linked Medicare data as the reference standard to determine the extent by which mortality is underestimated in NHATS through use of its Sensitive files. Ascertainment of mortality was compared between the 2 strategies over 10 years for 7 608 members of the 2011 cohort and 5 years for 7 498 members of the 2015 cohort.
Results:
The Sensitive files did not identify a large number of decedents, leading to suboptimal sensitivity, ranging from 61.3% (2011 cohort, 10 years) to 75.5% (2015 cohort, 5 years). Some non-decedents were also misclassified as dead using the Sensitive files. Cumulative mortality rates were modestly lower for this ascertainment strategy, although the number of participants at risk decreased markedly over time. Mortality incidence rates were also modestly lower for this strategy, with incidence rate ratios ranging from 0.88 (2011 cohort, 10 years) to 0.94 (2011 cohort, 5 years).
Conclusions:
Use of the NHATS Sensitive files leads to incomplete ascertainment and, to a lesser degree, misclassification of mortality. Caution may be warranted when interpreting results of longitudinal analyses in NHATS that evaluate mortality using the Sensitive files.
More Related Videos
06:55Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
08:53Author Spotlight: Automated Lifespan Monitoring – Discovering Aging Dynamics with the Lifespan Machine
Published on: January 26, 2024
Related Concept Videos
Longitudinal Research
Actuarial Approach
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
Assumptions of Survival Analysis
Kaplan-Meier Approach
Longitudinal Studies
Truncation in Survival Analysis
Left truncation occurs when individuals who experienced the event of interest before a certain time are not included in the study. This is often due to a "delayed entry" into the study where only those who survive until a certain entry point are...