Using Animations of Risk Functions to Visualize Trends in US All-Cause and Cause-Specific Mortality, 1968–2016
Bibliographic Data
Objectives. To use dynamic visualizations of mortality risk functions over both calendar year and age as a way to estimate and visualize patterns in US life spans. Methods. We built 49 synthetic cohorts, 1 per year 1968 to 2016, using National Center for Health Statistics (NCHS) mortality and population data. Within each cohort, we estimated age-specific probabilities of dying from any cause (all-cause analysis) or from a particular cause (cause-specific analysis). We then used Kaplan–Meier (all-cause) or Aalen–Johansen (cause-specific) estimators to obtain risk functions. We illustrated risk functions using time-lapse animations. Results. Median age at death increased from 75 years in 1970 to 83 years in 2015. Risk by age 100 years of cardiovascular mortality decreased (from a risk of 55% in 1970 to 32% in 2015), whereas risk attributable to other (i.e., nonrespiratory and noncardiovascular) causes increased in compensation. Conclusions. Our findings were consistent with the trends published in the NCHS 2015 mortality report, and our dynamic animations added an efficient, interpretable tool for visualizing US mortality trends over age and calendar time
Cause of death · Cohort · Disease · Environmental health · Health statistics · Pathology · Population · Data Visualization and Analytics · Demography · Insurance, Mortality, Demography, Risk Management · Machine Learning in Healthcare · Medicine · Gerontology
| Citations per year | 0.2 |
|---|---|
| Citation span | 2021 - 2021 (1) |
| Highly cited | No |