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. 2022 Jan 10;12(1):459.
doi: 10.1038/s41598-021-04016-x.

Cross-classification between self-rated health and health status: longitudinal analyses of all-cause mortality and leading causes of death in the UK

Julian Mutz  1 , Cathryn M Lewis  2   3
Affiliations

Cross-classification between self-rated health and health status: longitudinal analyses of all-cause mortality and leading causes of death in the UK

Julian Mutz et al. Sci Rep. .

Abstract

Risk stratification is an important public health priority that is central to clinical decision making and resource allocation. The aim of this study was to examine how different combinations of self-rated and objective health status predict all-cause mortality and leading causes of death in the UK. The UK Biobank study recruited > 500,000 participants between 2006 and 2010. Self-rated health was assessed using a single-item question and health status was derived from medical history, including data on 81 cancer and 443 non-cancer illnesses. Analyses included > 370,000 middle-aged and older adults with a median follow-up of 11.75 (IQR = 1.4) years, yielding 4,320,270 person-years of follow-up. Compared to individuals with excellent self-rated health and favourable health status, individuals with other combinations of self-rated and objective health status had a greater mortality risk, with hazard ratios ranging from HR = 1.22 (95% CI 1.15-1.29, PBonf. < 0.001) for individuals with good self-rated health and favourable health status to HR = 7.14 (95% CI 6.70-7.60, PBonf. < 0.001) for individuals with poor self-rated health and unfavourable health status. Our findings highlight that self-rated health captures additional health-related information and should be more widely assessed. The cross-classification between self-rated health and health status represents a straightforward metric for risk stratification, with applications to population health, clinical decision making and resource allocation.

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Conflict of interest statement

JM receives studentship funding from the Biotechnology and Biological Sciences Research Council (BBSRC) and Eli Lilly and Company Limited. CML is a member of the Scientific Advisory Board of Myriad Neuroscience.

Figures

Figure 1
Figure 1
Kaplan–Meier survival probabilities for all-cause mortality. Full health cross-classification, self-rated health and health status. 89 observations were above graph maximum of age 83.
Figure 2
Figure 2
All-cause mortality by health cross-classification stratified by sex. Hazard ratios (HR) with 95% confidence intervals from Cox proportional hazards models. Model 1—unadjusted; Model 2—adjusted for sociodemographic characteristics (excluding sex); Model 3—additionally adjusted for lifestyle factors.
See this image and copyright information in PMC

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