Mortality prediction with a single general self-rated health question

A meta-analysis
  • Karen B. DeSalvo
  • Nicole Bloser
  • Kristi Reynolds
  • Jiang He
  • Paul Muntner
Clinical Review

Abstract

OBJECTIVE: Health planners and policy makers are increasingly asking for a feasible method to identify vulnerable persons with the greatest health needs. We conducted a systematic review of the association between a single item assessing general self-rated health (GSRH) and mortality.

DATA SOURCES: Systematic MEDLINE and EMBASE database searches for studies published from January 1966 to September 2003.

REVIEW METHODS: Two investigators independently searched English language prospective, community-based cohort studies that reported (1) all-cause mortality, (2) a question assessing GSRH; and (3) an adjusted relative risk or equivalent. The investigators searched the citations to determine inclusion eligibility and abstracted data by following a standarized protocol. Of the 163 relevant studies identified, 22 cohorts met the inclusion criteria. Using a random effects model, compared with persons reporting “excellent” health status, the relative risk (95% confidence interval) for all-cause mortality was 1.23 [1.09, 1.39], 1.44 [1.21, 1.71], and 1.92 [1.64, 2.25] for those reporting “good,” “fair,” and “poor” health status, respectively. This relationship was robust in sensitivity analyses, limited to studies that adjusted for comorbid illness, functional status, cognitive status, and depression, and across subgroups defined by gender and country of origin.

CONCLUSIONS: Persons with “poor” self-rated health had a 2-fold higher mortality risk compared with persons with “excellent” self-rated health. Subjects’ responses to a simple, single-item GSRH question maintained a strong association with mortality even after adjustment for key covariates such as functional status, depression, and co-morbidity.

Key words

meta-analysis mortality risk assessment self-rated health quality of life 

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Copyright information

© Society of General Internal Medicine 2006

Authors and Affiliations

  • Karen B. DeSalvo
    • 1
    • 2
    • 3
  • Nicole Bloser
    • 1
    • 2
  • Kristi Reynolds
    • 2
  • Jiang He
    • 1
    • 2
  • Paul Muntner
    • 1
    • 2
  1. 1.Section of General Internal MedicineTulane University School of MedicineNew Orleans
  2. 2.Department of EpidemiologyTulane University School of Public Health and Tropical MedicineNew OrleansUSA
  3. 3.Department of Health Systems ManagementTulane University School of Public Health and Tropical MedicineNew OrleansUSA

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