Index to Predict 5-Year Mortality of Community-Dwelling Adults Aged 65 and Older Using Data from the National Health Interview Survey
Open accessAbstract
Background Prognostic information is becoming increasingly important for clinical decision-making.Objective To develop and validate an index to predict 5-year mortality among community-dwelling older adults.Design and participants A total of 24,115 individuals aged >65 who responded to the 1997-2000 National Health Interview Survey (NHIS) with follow-up through 31 December 2002 from the National Death Index; 16,077 were randomly selected for the development cohort and 8,038 for the validation cohort.Measurements 39 risk factors (functional measures, illnesses, behaviors, demographics) were included in a multivariable Cox proportional hazards model to determine factors independently associated with mortality. Risk scores were calculated for participants using points derived from the final model's beta coefficients. To evaluate external validity, we compared survival by quintile of risk between the development and validation cohorts.Results Seventeen percent of participants had died by the end of the study. The final model included 11 variables: age (1 point for 70-74 up to 7 points for >85); male: 3 points; BMI <25: 2 points; perceived health (good: 1 point, fair/poor: 2 points); emphysema: 2 points; cancer: 2 points; diabetes: 2 points; dependent in instrumental activities of daily living: 2 points; difficulty walking: 3 points; smoker-former: 1 point, smoker-current: 3 points; past year hospitalizations-one: 1 point, >2: 3 points. We observed close agreement between 5-year mortality in the two cohorts; which ranged from 5% in the lowest risk quintile to 50% in the highest risk quintile in the validation cohort.Conclusions This validated mortality index can be used to account for participant life expectancy in analyses using NHIS data.
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Mortality prediction models that account for variables such as comorbidities and functional status can serve as the basis for making more refined life expectancy estimates.
“Mortality prediction models that account for variables such as comorbidities and functional status can serve as the basis for making more refined life expectancy estimates107–109.”
From Diabetes in Older Adults: A Consensus Report (2012) · cites this paper as [109]
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- Authors
- Schonberg, M. A., Davis, R. B., McCarthy, E. P., & Marcantonio, E. R.
- Affiliations
- Beth Israel Deaconess Medical Center (US)
- Corresponding author
- Schonberg, Mara A.
- Venue
- Journal of General Internal Medicine
- Published
- 2009-08-01
- Volume
- 24
- Issue
- 10
- Pages
- 1115-1122
- ISSN
- 0884-8734 (ISSN-L)
- 1525-1497
- PMC
- PMC2762505
- OpenAlex
- W2069211921
- Cited by
- 214
- References
- 30
- Citations by year
- 2026: 9 · 2025: 10 · 2024: 10 · 2023: 19 · 2022: 15 · 2021: 14 · 2020: 12 · 2019: 11 · 2018: 13 · 2017: 16 · 2016: 25 · 2015: 14 · 2014: 12 · 2013: 9 · 2012: 14
- Type
- paratext
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Journal of General Internal Medicine (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institute on Aging (K23AG028584)
- Topics
- Health Sciences › Medicine › Geriatrics and Gerontology › Frailty in Older Adults
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Aging, Health, and Disability
- Health Sciences › Medicine › Epidemiology › Chronic Disease Management Strategies
- Keywords
- mortality prediction, older adults, community-dwelling adults, 5-year mortality, risk score, prognostic factors, functional status, instrumental activities of daily living, health perception, emphysema, diabetes mellitus, cancer, smoking, hospitalization, life expectancy, National Health Interview Survey
- MeSH terms
- Age Factors, Aged, Aged, 80 and over, Female, Follow-Up Studies, Forecasting, Health Status Indicators, Health Surveys, Humans, Male, Mortality, Residence Characteristics, Statistics as Topic, United States, Reproducibility of Results, Cohort Studies, Survival Rate
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