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International Journal of Environmental Research and Public Health logoLink to International Journal of Environmental Research and Public Health
. 2023 Feb 21;20(5):3813. doi: 10.3390/ijerph20053813

Self-Rated Health as a Predictor of Mortality in Older Adults: A Systematic Review

Moustapha Dramé 1,2,*, Eléonore Cantegrit 3, Lidvine Godaert 1,3
Editors: Tamara Alhambra Borrás, Ascensión Doñate-Martínez
PMCID: PMC10001164  PMID: 36900823

Abstract

The aim of this study was to investigate the link between self-reported health (SRH) and mortality in older adults. In total, 505 studies were found in PubMed and Scopus, of which 26 were included in this review. In total, 6 of the 26 studies included did not find any evidence of an association between SRH and mortality. Of the 21 studies that included community dwellers, 16 found a significant relationship between SRH and mortality. In total, 17 studies involved patients with no specific medical conditions; among these, 12 found a significant link between SRH and mortality. Among the studies in adults with specific medical conditions, eight showed a significant association between SRH and mortality. Among the 20 studies that definitely included people younger than 80 years, 14 found a significant association between SRH and mortality. Of the twenty-six studies, four examined short-term mortality; seven, medium-term mortality; and eighteen, long-term mortality. Among these, a significant association between SRH and mortality was found in 3, 7, and 12 studies, respectively. This study supports the existence of a significant relation between SRH and mortality. A better understanding of the components of SRH might help guide preventive health policies aimed at delaying mortality in the long term.

Keywords: self-rated health, mortality, older adults, prediction

1. Introduction

Numerous studies have investigated the predictive value of self-reported health (SRH) on mortality or adverse health outcomes in both young and old adults [1,2,3]. Overall, the results of these studies, particularly regarding the link between SRH and mortality, widely vary according to the age and sex of the population studied, the length of follow-up, or the presence or absence of specific diseases [4]. It is, therefore, difficult to know with any certainty what weight should be given to patients’ SRH. This difficulty is particularly marked among older adults, who are often frail and multimorbid, and who may have a life expectancy that is limited by one or more chronic diseases. SRH is a valuable assessment, because it covers multiple components and is easy to collect. Several authors [5,6] have shown the multiple domains are encompassed by the term self-reported health. However, the contribution of each individual component to the overall evaluation remains to be determined and seems to vary according to the context (gender, socio-economic or educational level, age category, religion, etc.). The evaluation of SRH yields a more comprehensive view of an individual’s health and may be more accurate than a purely medical evaluation. Moreover, it allows physicians to understand complex predictive factors of health, such as chronic inflammatory status [7,8]. Finally, SRH can be evaluated by asking a single, simple question [9].

In this systematic review, we aimed to determine whether there is a significant link between SRH and mortality in older adults.

2. Methods

2.1. Search Strategy

Before launching the literature search, we ensured that no systematic review had previously been conducted on this specific topic and in this particular population, by means of verification in PubMed, Scopus, Prospero, and the Cochrane library.

This was only a systematic review. A comprehensive literature search was performed in PubMed and Scopus. The search covered all publications up to and including 23 March 2022, with no specific start date specified. Search terms were defined by two senior researchers (L.G. and M.D.) and included the following keywords in the title and/or the abstract: (“obesity paradox” OR “reverse epidemiology” OR “body mass index”) AND (mortality OR death OR survival) (“self-rated health” OR “perceived health” OR “subjective health” OR “health report” OR “quality of life”) AND (mortality OR outcome OR survival OR death) AND (Age OR old OR elder*). Filters were applied to select studies in the English or French language and studies only including human subjects and to exclude the following publication types: reviews, case reports and case series, editorials, and correspondence. Reference lists were manually checked for additional studies. Study selection was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. This study was registered with PROSPERO (an International prospective register of systematic reviews), under the number CRD42022329082.

2.2. Study Selection Criteria

Study eligibility criteria were defined prior to performing the literature search by two senior researchers (L.G. and M.D.) according to the PICOS framework. Studies were eligible for inclusion if they reported data on self-rated health. The population of the studies included people aged 65 years or older, of any sex, ethnicity, or living place. The groups to be compared were defined according to their levels of self-rated health (SRH). The outcome was death, whatever the timepoint. Basic science articles, reviews, case reports and case series, editorials, and correspondence were excluded.

2.3. Data Extraction

Data analysis was performed using Covidence systematic review software© (Veritas Health Innovation, Melbourne, Australia), available at www.covidence.org (accessed on 23 March 2022). After eliminating duplicates, two senior researchers (L.G. and M.D.) independently reviewed the titles and abstracts of all articles. In case of disagreement about whether or not to include an article, the case was discussed until consensus was reached. Overlap between studies in the results reported was checked. We independently extracted the data, using the same data extraction form. For descriptive analyses, the following data were extracted: publication year, country where the study was conducted, study design, study setting, medical condition (if any), sample size, and age (mean or median and their statistical dispersion parameters, when available). To analyse the relation between SRH and mortality, the following information was collected: outcome (death or survival), type of analysis (whether adjusted or not), SRH levels, statistical estimates (hazard ratios, odds ratios, rate ratios, and rates) and their respective 95% confidence intervals (95% CIs), and the level of significance (p-values).

2.4. Quality Assessment

The quality of the included studies was assessed independently by two researchers (L.G. and M.D.) using the Newcastle–Ottawa Scale (NOS) [10]. The NOS consists of three quality parameters: selection, comparability, and outcome assessment. The “selection” criterion is scored between 0 and 4 points; the “comparability” criterion is scored between 0 and 2 points; and the “outcome” criterion is scored between 0 and 3 points. The sum of the scores of these three criteria gives an NOS total score between 0 and 9 points. NOS scores of 7 or over were considered to be of high quality, while 5–6 indicated moderate quality, and scores under 5 indicated low quality. Disagreement was resolved by means of a joint review of the manuscript to reach consensus, and the opinion of a third researcher was requested when necessary. When appropriate and possible, certain parameters were calculated from available data (e.g., pooled mean age and/or standard deviations, odds ratios, rate ratios, etc.).

3. Results

In total, 505 studies were identified during the literature search (Figure 1). Among these, 195 duplicates were excluded. After examination of the titles and abstracts of the remaining 310 studies, 98 articles were retained for full-text assessment. After reading the full text of these 98 studies, 72 were excluded for one or more of the following reasons: inappropriate age of the study population, wrong study design, or wrong outcome. Thus, 26 studies were included in the final review.

Figure 1.

Figure 1

PRISMA flow diagram of the records included in the systematic review.

Table 1 summarizes the characteristics of the studies included in the review. All studies were observational cohorts. The average age of the population included in the studies was >80 years in two articles [11,12] and was not specified in five articles [13,14,15,16,17]. The two articles [15,16] with a mean population age of over 80 were performed on the same cohort, with evaluation of mortality at different timepoints.

Table 1.

Description of the studies included in the present systematic review.

Author(s), Year Country Study Setting Medical Conditions Sample Size Age (Years)
Wuorela et al., 2020 [18] Finland Community No specific conditions (men only) 1008 70.0 ± 0.0 *
Godaert et al., 2018 [11] France Hospital, emergency Hospitalised for an acute condition 223 85.1 ± 5.5 *
Godard-Sebillotte et al., 2016 [12] France Hospital, emergency Hospitalised for an acute condition 223 85.1 ± 5.5 *
Mavaddat et al., 2016 [19] England and Wales Community including care homes No specific conditions 11,957 74.8 ± 6.6 *
Brown et al., 2015 [20] USA Community No specific conditions; exclusion of end-stage renal disease at baseline 191,001 75.0 ± x.x *
Gurland et al., 2014 [21] USA Community No specific conditions 2128 76.0 ± 5.8 *
Shen et al., 2014 [15] Hong Kong Health centres No specific conditions 66,814 ≥65
Fernández-Ruiz et al., 2013 [22] Spain Community No specific conditions 4958 74.1 ± 6.8 *
Puts et al., 2013 [2] Canada Hospital Cancer 112 74.2 ± 6.0 *
Ernstein et al., 2011 [23] Norway Community No specific conditions; exclusion of cardiovascular disease at baseline 5808 76.0 ± 4.9 *
Khang et al., 2010 [24] Korea Community No specific conditions 1448 ≥65
Ford et al., 2008 [25] Australia Community No specific conditions (women only) 12,422 70–75
Johansson et al., 2008 [26] Sweden Community Presence of signs or symptoms associated with chronic heart failure 448 73.0 ± 5.6 *
Okamoto et al., 2008 [27] Japan Community No specific conditions 784 ≥65
Lee et al., 2007 [28] USA Community No specific conditions 6298 ≥70
Van den Brink et al., 2005 [29] Finland, Italy, and Netherlands Community No specific conditions (men only) 1141 76.5 ± 4.4 *
Baron-Epel et al., 2004 [30] Israel Community No specific conditions 1138 77.5 (70–101) #
Walker et al., 2004 [31] Canada Community No specific conditions 8697 75.7 ± 7.1 *
Bath, 2003 [32] UK Community No specific conditions 1042 ≥65
Helmer et al., 1999 [33] France Community No specific conditions 3660 75.2 (65–101) #
Yu et al., 1998 [17] Shanghai Community No specific conditions 3094 ≥65
Leung et al., 1997 [34] Taiwan Long-term facility No specific conditions 411 77.5 ± x.x *
Schoenfeld et al., 1994 [35] USA Community Aging successfully 1037 70–79
Tsuji et al., 1994 [16] Japan Community No specific conditions 2252 65–113
Pijls et al., 1993 [13] Netherlands Community No specific conditions (men only) 783 65–85
Rakowski et al., 1993 [14] USA Community No specific conditions 5630 ≥70

* mean ± standard deviation; # mean (range); range; x: not defined.

The main results of the included studies are summarized in Table 2. As shown in Table 2, 6 of the 26 studies did not find any evidence of an association between SRH and mortality [2,25,27,29,32,33]. Among the 21 studies that included community dwellers, 16 found a significant relationship between worse SRH and higher mortality rates [13,14,16,17,18,19,20,21,22,23,24,26,28,30,31,35]. A total of 17 studies involved patients with no specific medical conditions; among them, 12 found a significant link between worse SRH and higher mortality rates [13,14,15,16,17,18,19,20,21,22,24,30]. Among the studies including individuals with specific medical conditions, eight showed a significant association between SRH and mortality [11,12,23,26,28,31,34,35]. When only specific mortality was considered (six studies), the relationship with SRH was always significant [13,15,16,17,23,26]. Two studies involved people over the age of 80 years. They both showed a significant association between SRH and mortality [11,12]. Among the 20 studies that definitely included people younger than 80 years (but older than 65), 14 found a significant association between SRH and mortality [17,18,19,20,21,22,23,24,26,28,30,31,34,35]. Of the 26 studies, 4 examined short-term mortality (<one year), while 7 examined medium-term mortality (one to five years), and 18 studied long-term mortality (five years or over). Of these, a significant association between SRH and mortality was found in 3 [11,12,20], 7 [11,16,19,20,28,34,35], and 12 studies [13,14,15,17,18,21,22,23,24,26,30,31], respectively. When SRH was considered as a dichotomous variable (in 11 studies), it was significantly associated with mortality in 9 cases [11,12,18,19,23,24,28,30,31], and when considered as a non-dichotomous variable (in 17 studies), the association between worse SRH and higher mortality rates was significant in 12 cases [13,14,15,16,17,18,20,21,22,26,34,35].

Table 2.

Outcome and results of association between SRH and mortality in aged adults.

Author(s), Year Outcome Medical
Conditions
Analysis Results
SRH Levels Estimates
(95% CI)
p
Wuorela et al., 2020 [18] 5-year mortality No specific conditions aHR Good/rather good Reference
Poor 2.17 (1.42–3.31) <0.001
10-year mortality Good Reference
Rather good 2.29 (1.24–4.23) 0.009
Poor 4.08 (2.14–7.77) <0.001
27-year mortality Good Reference
Rather good 1.19 (0.94–1.51) 0.14
Poor 1.62 (1.23–2.13 <0.001
Godaert et al., 2018 [11] 6-month mortality Hospitalised for an acute condition aHR Very good/good Reference
Medium to very poor 2.7 (1.6–4.7) 0.0003
1-year mortality Very good/good Reference
Medium to very poor 2.4 (1.5–4.0) 0.0006
2-year-mortality Very good/good Reference
Medium to very poor 1.9 (1.3–2.9) 0.002
3-year mortality Very good/good Reference
Medium to very poor 1.6 (1.1–2.4) 0.01
Godard-Sebillotte et al., 2016 [12] 6-week mortality Hospitalised for an acute condition aHR Very good/good Reference
Medium to very poor 2.61 (1.18–5.77) 0.02
Mavaddat et al., 2016 [19] 2-year mortality No specific conditions, no prior history of stroke aOR Excellent/good Reference
Fair/poor 1.7 (1.4–2.0) S
No specific conditions, prior history of stroke Excellent/good Reference
Fair/poor 1.1 (0.7–1.8) NS
13-year mortality No specific conditions, no prior history of stroke aHR Excellent Reference
Good 1.2 (1.0–1.4) S
Fair 1.3 (1.1–1.6) S
Poor 1.2 (0.9–1.7) NS
No specific conditions, prior history of stroke Excellent Reference
Good 0.8 (0.5–1.3) NS
Fair 0.8 (0.4–1.3) NS
Poor 1.1 (0.6–2.1) NS
Brown et al., 2015 [20] 90-day mortality No specific conditions, no end-stage renal disease aHR Excellent Reference
Very good 1.00 (0.56–1.78) NS
Good 1.65 (0.95–2.85) NS
Fair 3.03 (1.73–5.30) <0.001
Poor 7.36 (4.08–13.25) <0.001
Maximum follow-up mortality (>2.5 years) aHR Excellent Reference
Very good 1.13 (1.01–1.27) <0.05
Good 1.60 (1.43–1.79) <0.001
Fair 2.52 (2.25–2.83) <0.001
Poor 4.24 (3.73–4.82) <0.001
Gurland et al., 2014 [21] 16-year survival No specific conditions aHR Poor Reference
Excellent 0.69 (0.54–0.89) S
Good 0.79 (0.63–0.99) S
Fair 0.77 (0.62–0.96) S
Shen et al., 2014 [15] 10-year all-cause mortality No specific conditions aHR Better Reference
Normal 0.86 (0.81–0.91) S
Worse 0.91 (0.86–0.96) S
10-year cardiovascular disease mortality Better Reference
Normal 0.85 (0.77–0.94) S
Worse 0.84 (0.76–0.94) S
10-year stroke mortality Better Reference
Normal 0.83 (0.70–0.99) S
Worse 0.88 (0.76–1.05) NS
10-year ischemic heart disease mortality Better Reference
Normal 0.88 (0.74–1.03) NS
Worse 0.84 (0.71–0.99) S
10-year all-cancer mortality Better Reference
Normal 0.90 (0.81–0.99) S
Worse 0.97 (0.87–1.08) NS
10-year all-respiratory disease mortality Better Reference
Normal 0.85 (0.75–0.96) S
Worse 0.93 (0.82–1.06) NS
Fernández-Ruiz et al., 2013 [22] 13-year all-cause mortality No specific conditions aHR Very good Reference
Good 0.95 (0.81–1.12) NS
Fair 1.22 (1.03–1.44) <0.05
Poor/very poor 1.39 (1.15–1.69) <0.01
Puts et al., 2013 [2] 12-month mortality Newly diagnosed cancer aHR Good/excellent Reference
Fair/poor/very poor 1.33 (0.50–3.53) NS
Ernstein et al., 2011 [23] 10-year IHD mortality No specific conditions; exclusion of cardiovascular disease at baseline (men) aHR Very good/good Reference
Fair/poor 1.23 (0.91–1.67) NS
No specific conditions; exclusion of cardiovascular disease at baseline (women) Very good/good Reference
Fair/poor 1.61 (1.14–2.29) S
10-year all-cause mortality No specific conditions; exclusion of cardiovascular disease at baseline (men) Very good/good Reference
Fair/poor 1.42 (1.25–1.61) S
No specific conditions; exclusion of cardiovascular disease at baseline(women) Very good/good Reference
Fair/poor 1.60 (1.39–1.84) S
Khang et al., 2010 [24] Long-term mortality No specific conditions, non-institutionalized population, men aHR Very good/good/fair Reference
Very poor/poor 2.21 (1.47–3.33) S
No specific conditions, non-institutionalized population (women) Very good/good/fair Reference
Very poor/poor 2.05 (1.33–3.15) S
Ford et al., 2008 [25] Long-term mortality No specific conditions (women only) aHR Excellent Reference
Very good 1.04 (0.77–1.41) NS
Good 1.27 (0.95–1.70) NS
Fair 2.10 (1.56–2.83) S
Poor 3.83 (2.73–5.38) S
Johansson et al., 2008 [26] 10-year cardiovascular mortality Presence of signs or symptoms associated with chronic heart failure aHR Very good Reference
Good 3.4 (1.4–7.8) 0.005
Poor 4.1 (1.8–9.4) 0.001
Okamoto et al., 2008 [27] 6-year mortality No specific conditions (men) aHR Fair/Poor Reference 0.04 #
Good 0.63 (0.32–0.98)
Excellent 0.48 (0.14–1.07)
No specific conditions (women) Fair/poor Reference 0.40 #
Good 0.78 (0.41–1.33)
Excellent 0.74 (0.21–1.32)
Lee et al., 2007 [28] 4-year mortality No specific conditions (Black Americans of ≥80 years) aOR Good Reference
Poor 1.9 (1.1–3.2) S
No specific conditions (White Americans of ≥80 years) Good Reference
Poor 2.0 (1.7–2.5) S
Van den Brink et al., 2005 [29] 10-year mortality No specific conditions (only men born between 1900 and 1920) aHR Healthy Reference
Not healthy 1.19 (0.97–1.46) NS
Baron-Epel et al., 2004 [30] 91-month mortality No specific conditions (men) aHR Sub-optimal Reference
Optimal 1.33 (1.10–1.61) <0.01
No specific conditions (women) aHR Sub-optimal Reference
Optimal 1.40 (1.17–1.67) <0.01
Walker et al., 2004 [31] 5-year mortality No specific conditions, cognitively intact aHR Good Reference
Poor 1.57 (1.38–1.78) S
No specific conditions, mild to moderate cognitive impairment Good Reference
Poor 1.26 (1.01–1.59) S
No specific conditions, severe cognitive impairment Good Reference
Poor 1.00 (0.76–1.31) NS
Bath, 2003 [32] 4-year mortality No specific conditions (men) aHR Excellent Reference
Good 0.67 (0.35–1.29) NS
Average 1.17 (0.55–2.50) NS
Fair 0.62 (0.25–1.53) NS
Poor 0.87 (0.32–2.33) NS
No specific conditions (women) aHR Excellent Reference
Good 1.44 (0.63–3.29) NS
Average 1.15 (0.44–2.98) NS
Fair 1.13 (0.41–3.06) NS
Poor 1.98 (0.63–6.25) NS
12-year mortality No specific conditions (men) aHR Excellent Reference
Good 0.94 (0.66–1.34) NS
Average 1.16 (0.73–1.83) NS
Fair 1.01 (0.61–1.66) NS
Poor 1.54 (0.84–2.83) NS
No specific conditions (women) aHR Excellent Reference
Good 1.09 (0.76–1.57) NS
Average 0.84 (0.54–1.31) NS
Fair 1.17 (0.75–1.84) NS
Poor 1.30 (0.72–2.36) NS
Helmer et al., 1999 [33] 5-year mortality No specific conditions aHR Very good Reference
Good 1.93 (1.15–3.23) <0.05
Fair 2.01 (1.16–3.46) <0.05
Bad/very bad 1.87 (0.99–3.55) NS
Yu et al., 1998 [17] 5-year mortality No specific conditions (aged 65–74 years) aHR Excellent/good Reference
Fair 2.16 (1.44–3.25) <0.001
Poor 1.93 (1.20–3.11) 0.007
No specific conditions (aged 75 years and older) Excellent/good Reference
Fair 1.14 (0.87–1.49) 0.338
Poor 1.34 (0.95–1.88) 0.092
Leung et al., 1997 [34] 3-year mortality No specific conditions (living in institutions) aHR Good Reference
Average 4.05 (0.93–17.70) NS
Fair/poor 6.00 (1.39–25.90) S
Schoenfeld et al., 1994 [35] 3-year mortality Aging successfully aOR Excellent Reference 0.0001 #
Good 2.69 (2.15–3.38)
Fair 7.26 (4.61–11.44)
Poor/bad 19.56 (9.89–38.68)
Tsuji et al., 1994 [16] 3-year all-cause mortality No specific conditions aHR Excellent/good Reference
Fair 2.23 (1.53–3.26) S
Poor 3.07 (1.50–6.26) S
3-year cancer mortality Excellent/good Reference
Fair 3.41 (1.86–6.24) S
Poor 13.61 (3.47–53.42) S
3-year stroke mortality Excellent/good Reference
Fair 2.44 (0.97–6.15) NS
Poor 2.48 (0.68–9.07) NS
3-year heart disease mortality Excellent/good Reference
Fair 0.96 (0.32–2.86) NS
Poor 1.34 (0.21–8.50) NS
Pijls et al., 1993 [13] 5-year all-cause mortality No specific conditions (men) aHR Healthy Reference <0.001 #
Rather healthy 1.3 (0.9–1.8)
Moderately healthy 2.4 (1.5–3.8)
Not healthy 5.4 (2.7–11.0)
5-year cardiovascular diseases mortality Healthy Reference 0.09 #
Rather healthy 1.3 (0.8–2.2)
Moderately healthy
/not healthy
1.9 (0.9–3.8)
5-year cancer mortality Healthy Reference 0.003 #
Rather healthy 1.1 (0.6–2.1)
Moderately healthy
/not healthy
4.2 (1.9–9.4)
Rakowski et al., 1993 [14] Long-term mortality No specific conditions OR Excellent Reference
Very good 1.22 (0.98–1.53) NS
Good 1.48 (1.21–1.82) S
Fair 2.40 (1.93–3.00) S
Poor 4.49 (3.50–5.77) S

95% CI, 95% confidence interval; aHR, adjusted hazard ratio; OR, non-adjusted odds ratio; aOR, adjusted odds ratio; S, significant; NS, not significant; # p for trend.

The quality of the included studies, as assessed using the NOS, is summarized in Table 3. The quality was considered high for all 26 studies.

Table 3.

Quality assessment of the different studies included in this systematic review performed using the Newcastle–Ottawa scale (NOS).

Author(s), Year Study Design Selection Comparability Outcome Total Score Quality Rating
Wuorela et al., 2020 [18] Longitudinal **** ** *** 9 High
Godaert et al., 2018 [11] Longitudinal **** ** *** 9 High
Godard-Sebillotte et al., 2016 [12] Longitudinal **** ** *** 9 High
Mavaddat et al., 2016 [19] Longitudinal *** ** *** 8 High
Brown et al., 2015 [20] Longitudinal *** ** *** 8 High
Gurland et al., 2014 [21] Longitudinal **** ** *** 9 High
Shen et al., 2014 [15] Longitudinal **** ** *** 9 High
Fernández-Ruiz et al., 2013 [22] Longitudinal **** ** *** 9 High
Puts et al., 2013 [2] Longitudinal *** ** *** 8 High
Ernstein et al., 2011 [23] Longitudinal *** ** *** 8 High
Khang et al., 2010 [24] Longitudinal *** ** ** 7 High
Ford et al., 2008 [25] Longitudinal *** ** *** 8 High
Johansson et al., 2008 [26] Longitudinal *** ** *** 8 High
Okamoto et al., 2008 [27] Longitudinal **** ** *** 9 High
Lee et al., 2007 [28] Longitudinal **** ** *** 9 High
Van den Brink et al., 2005 [29] Longitudinal *** ** *** 8 High
Baron-Epel et al., 2004 [30] Longitudinal **** ** *** 9 High
Walker et al., 2004 [31] Longitudinal **** ** *** 9 High
Bath, 2003 [32] Longitudinal **** ** *** 8 High
Helmer et al., 1999 [33] Longitudinal **** ** *** 9 High
Yu et al., 1998 [17] Longitudinal **** ** *** 9 High
Leung et al., 1997 [34] Longitudinal ** ** *** 7 High
Schoenfeld et al., 1994 [35] Longitudinal **** ** *** 9 High
Tsuji et al., 1994 [16] Longitudinal *** ** *** 8 High
Pijls et al., 1993 [13] Longitudinal *** ** *** 8 High
Rakowski et al., 1993 [14] Longitudinal **** ** *** 9 High

NOS scores ≥7 were considered to indicate high-quality studies, and scores of 5–6 indicated moderate quality. The sum of the stars constitutes the Total score (for the first row: 4 stars for selection, two stars for Comparability, and three stars for outcome equal 9 stars (total score equals 9).

4. Discussion

In this systematic review of the predictive relationship between self-rated health (SRH) and mortality in people aged 65 years or over, we included 26 studies [2,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35], of which 4 investigated short-term mortality (≤1 year) [2,11,12,20], 8 investigated medium-term (>1 year and <5 years) mortality [11,16,19,20,28,32,34,35], and 18 investigated long-term mortality (≥5 years) [13,14,15,17,18,19,21,22,23,24,25,26,27,29,30,31,32,33]. Five articles studied the relationship between SRH and mortality at several timepoints [11,18,19,20,32]. The majority of articles concerned populations without a specific medical condition at inclusion [13,14,15,16,17,18,19,20,21,22,24,25,27,29,30,32,33].

For the two studies that included people aged 80 years or over, the authors showed a significant relationship between SRH and all-cause mortality at each timepoint (6 weeks; 6 months; and 1, 2 and 3 years). However, it seems difficult to extrapolate these results, as they all concern the same population, hospitalised via the emergency department for an acute condition.

In the community-dwelling population, with a mean age of <80 years at inclusion, not selected for the presence of any specific pathology, our systematic review supports a predictive relationship between SRH and all-cause mortality at each time point. Of 17 articles [13,14,15,16,17,18,19,20,21,22,24,25,27,29,30,32,33] studying all-cause mortality, 12 [13,14,15,16,17,18,19,20,21,22,24,30] found a predictive relationship between SRH and death (i.e., 70.5% of the articles studied). Three articles [16,19,20] were specific to medium-term and nine [13,14,15,17,18,21,22,24,30] to long-term all-cause mortality. These results are consistent with previous studies of younger adults showing that SRH is predictive of all-cause mortality in the medium (<5 years) [36,37] and long term [3]. The persistence of a long-term predictive link is remarkable in the elderly population, as these are often fragile individuals, with multiple causes of death.

SRH is a composite concept that encompasses medical, social, cultural, religious, ethnical, and individual dimensions. Several authors have attempted to characterise the different dimensions of health under the term “SRH” [1,5,6,38,39,40]. The share of each dimension in the overall subjective feeling varies from one individual to another, explaining the variable strength of the link between SRH and mortality according to gender, culture, ethnicity, socio-economic level. and even age group [33,36,41,42,43]. Zajacova et al. [44] showed that the individual criteria taken into account when assessing SRH varied from one sex to another as well as according to the period of life. Younger women tended to assess their SRH more unfavourably than men of the same age, while older women had a more favourable view of their SRH than men of the same age. This trend is even more salient if socio-economic factors (such as education, marital status, or income) are taken into account. As people age, the SRH is generally poorer, in both sexes, and this worsens as health problems and loss of autonomy increase. This illustrates the likely important role of medical criteria and functional status in the assessment of SRH with advancing age. Zajacova et al. [44] pointed out that all health indicators (physical health such as functioning or pain, mental health such as depressive symptoms, and health behaviours) are significantly associated with SRH, regardless of age or sex. Cott et al. [45] made the same observation in adult populations with one or more chronic diseases.

SRH is also associated with other factors known to predict outcome in the elderly population, such as interkeukin-6 (IL-6) [7]. Arnberg et al. [7] found that good or very good SRH was associated with low levels of systemic markers of inflammation in a population with a median age of 74 years (range of 60–93 at inclusion). Christian et al. [8] reported similar findings. Taken together, these data confirm that the collection of SRH in routine practice would be a simple and effective way of complementing the usual medical assessment to extrapolate an individual’s life trajectory.

Throughout life, including in the older population, the SRH seems to be a fairly accurate assessment of an individual’s functional capacities and even functional reserves for coping with the hazards of life, as evidenced by the predictive link with all-cause mortality demonstrated at all ages of adult life and at all timepoints. SRH is easily collected [9], even in people with mild-to-moderate cognitive impairment [31,46].

The methods used to collect SRH are variable. In our systematic review, some authors chose to assess the SRH on a value scale from excellent to very poor (excellent, very good, good, fair, poor, and very poor). Others chose to class SRH on a binary scale (SRH (excellent, very good or good) versus (fair, poor or very poor)). Of the 11 authors who evaluated SRH on a binary scale, 9 (i.e., 81.8%) found a predictive link between SRH and mortality in the short, medium, or long term [11,12,18,19,23,24,28,30,31]. Among the authors who treated the SRH according to a multiple choice scale, 12 (i.e., 70.6%) [13,14,15,16,17,18,20,21,22,26,34,35] showed a predictive link between SRH and mortality for at least one time point. The predictive capacity of the SRH with respect to mortality seems to be better when SRH is treated as a binary variable, most likely because there is greater statistical power with a dichotomous variable than with a non-binary, categorical one.

The predictive link between SRH and specific mortality in specific medical conditions seems to be more difficult to establish, because it is less well documented. In this systematic review, three articles investigated mortality linked to cancer [13,15,16], and two of them found a significant predictive relationship between SRH and cancer-related death in the medium [16] and long term [13]. Five articles investigated cardiovascular mortality [13,15,16,23,26], of which four [13,15,23,26] found that SRH significantly predicted cardiovascular death in the long term in a population with a mean age of <80 years.

5. Conclusions

SRH seems to be a good criterion for assessing the risk of mortality in the short, medium, or long term in a population of elderly subjects living at home according to the articles studied in this systematic review. SRH assessment is complementary to so-called objective medical measures. SRH is simple to collect, which makes it easy to use for health professionals and acceptable to the population. Its composite nature makes it possible to take into account an individual’s health in a global manner.

A better understanding of the components of SRH and their respective weight at each age might help to guide preventive health policies aimed at delaying mortality in the long term. However, there are currently no studies that have established that improving the criteria comprising SRH would make it possible to reduce mortality.

Moreover, as the weight of each criterion seems to vary according to the individual and the age considered, targeted interventions may not be very effective. The composite nature of the SRH concept should encourage us to implement comprehensive prevention strategies from the outset, individualised and variable over time for greater effectiveness.

Prevention strategies should be implemented early in the life of the individual and continue throughout life. The identification of poor SRH in a patient should prompt healthcare providers to promptly look for associated modifiable factors in an attempt to improve them.

Acknowledgments

To Fiona Ecarnot (University of Franche-Comté, Besançon, France), for editorial assistance.

Author Contributions

Conceptualization, L.G. and M.D.; Methodology, M.D. and L.G.; Software, M.D. and L.G.; Validation, M.D., E.C. and L.G.; Formal analysis, M.D. and L.G.; Writing—original draft preparation, M.D. and L.G.; Writing—review and editing, M.D., E.C. and L.G. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data can be make available at moustapha.drame@chu-martinique.fr.

Conflicts of Interest

The authors declare no conflict of interest related to this work.

Funding Statement

This research received no external funding.

Footnotes

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

Data can be make available at moustapha.drame@chu-martinique.fr.


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