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. 2023 Apr 6;15(7):1780. doi: 10.3390/nu15071780

The Obesity Paradox and Mortality in Older Adults: A Systematic Review

Moustapha Dramé 1,2,*, Lidvine Godaert 1,3
Editor: Lindsay Brown
PMCID: PMC10096985  PMID: 37049633

Abstract

“Obesity paradox” describes the counterintuitive finding that aged overweight and obese people with a particular disease may have better outcomes than their normal weight or underweight counterparts. This systematic review was performed to summarize the publications related to the obesity paradox in older adults, to gain an in-depth understanding of this phenomenon. PubMed©, Embase©, and Scopus© were used to perform literature search for all publications up to 20 March 2022. Studies were included if they reported data from older adults on the relation between BMI and mortality. The following article types were excluded from the study: reviews, editorials, correspondence, and case reports and case series. Publication year, study setting, medical condition, study design, sample size, age, and outcome(s) were extracted. This review has been registered with PROSPERO (no. CRD42021289015). Overall, 2226 studies were identified, of which 58 were included in this systematic review. In all, 20 of the 58 studies included in this review did not find any evidence of an obesity paradox. Of these 20 studies, 16 involved patients with no specific medical condition, 1 involved patients with chronic diseases, and 2 involved patients with type 2 diabetes mellitus. Seven out of the nine studies that looked at short-term mortality found evidence of the obesity paradox. Of the 28 studies that examined longer-term mortality, 15 found evidence of the obesity paradox. In the studies that were conducted in people with a particular medical condition (n = 24), the obesity paradox appeared in 18 cases. Our work supports the existence of an obesity paradox, especially when comorbidities or acute medical problems are present. These findings should help guide strategies for nutritional counselling in older populations.

Keywords: obesity paradox, aged adults, body mass index, mortality

1. Introduction

Obesity, usually defined by the body mass index (BMI), is considered a public health problem, and is associated with many diseases [1,2,3]. The prevalence of obesity is high in younger adults but also in older people [4], and evidence suggests that prevalence of obesity will continue to increase [5]. The term “obesity paradox” is used to describe the counterintuitive finding that aged overweight and obese people with a particular disease may have better outcomes than their normal weight or underweight counterparts. However, there is wide heterogeneity between studies regarding the association between obesity and mortality in older adults, depending on the diseases concerned, the presence or absence of a particular disease, or the BMI level considered [6,7,8]. In aged people, body composition tends to change, and body weight tends to decrease, and some authors have suggested that fatness could be healthy [9]. Thus, it is important to confirm whether an “obesity paradox” truly exists, with a view to adapting management policies for overweight or obese old people.

In this context, the objective of the study was to summarize the publications in the literature relating to the obesity paradox in older adults, to enhance our understanding of this phenomenon.

2. Methods

2.1. Literature Search

A preliminary check was made in PubMed©, Scopus©, Embase©, Prospero©, and the Cochrane Library© to ensure that no systematic reviews had previously been conducted on this specific topic.

A literature search was performed using PubMed©, Embase©, and Scopus© to cover all publications up to March 20, 2022. The search terms defined by the two researchers (LG, MD) included the following keywords in the title and/or the abstract: (“obesity paradox” OR “reverse epidemiology” OR “body mass index” OR BMI OR overweight OR obesity) AND (mortality OR death OR survival)). The search included studies in the French or English language and studies on human subjects, and excluded the following publication types: reviews, editorials, correspondence, and case reports and case series. A manual check was performed for potential additional studies. This systematic review was based on 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) (number CRD42021289015), available at https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021289015, accessed on 20 March 2023.

2.2. Study Selection

Study eligibility criteria were defined a priori by the two researchers (LG, MD) within the PICOS framework. Studies were eligible if they reported data on “obesity paradox” (using body mass index as a nutritional indicator). The population was restricted to studies that included persons 65 years or older, whatever their sex, ethnicity, or living place. The intervention (exposure) was a presence of overweight or obesity as defined by the baseline BMI value. The control was those who were underweight or a normal weight. The outcome was death, whatever the timepoint. When the study was not specifically conducted in older adults, only data concerning those aged 65 years or over were taken into account (provided that the information was available). Correspondence, editorials, reviews, basic science articles, and case reports and case series were excluded.

2.3. Data Extraction

The Covidence systematic review software© (Veritas Health Innovation, Melbourne, Australia), available at www.covidence.org, was used to perform data analysis. After elimination of duplicates, the two researchers (LG, MD) made a blind review of titles and abstracts of all articles. When there was disagreement about whether or not to include an article, they discussed the case until consensus was reached. Overlap between studies was verified. Data extraction was realised independently by the two researchers (LG, MD), using the same extraction form. The following data were extracted: publication year, study setting, medical condition, study design, sample size, age (mean or median and their statistical dispersion parameters, when available), and outcome(s). To check whether the obesity paradox was present or not, the following information was collected: outcome(s), BMI classes, type of analysis (whether multivariable or not), statistical estimates (Hazard ratio, Odds ratio, Rate ratio, Rates) and their respective 95% confidence intervals (95% CI), and the level of significance (p-values).

2.4. Quality Assessment

The Newcastle–Ottawa Scale (NOS) [10] was used to assess the quality of included studies. This scale is composed of three quality criteria: selection (4 points), comparability (2 points), and outcome assessment (3 points). This gives a total of between 0 and 9 points. Scores of 7 or more are considered high quality studies, scores of 5–6 as moderate quality, and scores below 5 as low quality. Disagreements in scoring were resolved by a joint review of the manuscript to reach consensus.

Where possible and appropriate, some parameters were calculated from available data (e.g., mean age and/or standard deviation, rate ratio, odds ratio, etc.).

3. Results

As shown in Figure 1, 2226 studies were identified by the literature search. Among these, 1285 duplicates were found and excluded. After checking titles and abstracts of the remaining 942 studies, 273 articles were included for full-text assessment. After full-text examination of these 273 studies, 215 were excluded for at least one of the following reasons: lack of relevant information, overlapping data, or inappropriate age of the study population. Thus, 58 studies were retained in this review.

Figure 1.

Figure 1

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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; 41 were prospective [11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51] and 17 were retrospective [52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68].

Table 1.

Description of the studies included in the present systematic review.

Author, Year Country Study Design Study Setting Medical Condition Sample Size Age (Years)
Mean ± SD
Kananen, 2022 [68] Sweden Retrospective cohort Hospital, Geriatrics COVID-19 1409 77 [65–104] ♣
Amin, 2021 [11] USA Prospective cohort Hospital, Surgery Hip fracture 52,729 x ± x
Danninger, 2021 [52] USA Retrospective cohort Hospital, ICU Sepsis 8707 x ± x
El Moheb, 2021 [12] USA Prospective cohort Hospital, Surgery Emergent surgery 78,704 75 ± x
Lin, 2021 [13] Taiwan Prospective cohort Community None specific 81,221 74 ± 6
Martinez-Tapia, 2021 [14] France Prospective cohort Hospital, Geriatrics Cancer 2071 81 ± 6
Lai, 2020 [15] Taiwan Prospective cohort LTCF None specific 182 79 ± 8
Schneider, 2020 [16] Germany Prospective cohort Hospital, Neurosurgery Glioblastoma 110 72 [65–86] ♣
Seino, 2020 [53] Japan Retrospective cohort Community None specific 1977 72 ± 6 *
Nishida, 2019 [17] Japan Prospective cohort Community None specific 1229 74 ± 5
Om, 2019 [18] Korea Prospective cohort Hospital, Cardiology Aortic stenosis 379 79 ± x *
Tokarek, 2019 [54] Poland Retrospective cohort Hospital, Cardiology TAVI patients 147 82 [x–x] ♣
Yoshihisa, 2019 [19] Japan Prospective cohort Hospital, Cardiology Acute heart failure 2410 x ± x
Crotti, 2018 [20] Italy Prospective cohort Community None specific 4970 72 ± 5
De Palma, 2018 [21] Sweden Prospective cohort Hospital, Cardiology TAVI patients 492 83 ± 6
Keller, 2018 [55] Germany Retrospective cohort Hospital, Cardiology AMI 122,607 80 ± x
Kim, 2018 [22] Korea Prospective cohort Community None specific 170,639 72 ± 5
Lee, 2018 [56] Korea Retrospective cohort Community None specific 11,844 72 ± 5
Lv, 2018 [23] China Prospective cohort Community None specific 4361 92 ± 8
de Souto Barreto, 2017 [24] France Prospective cohort Nursing home Dementia 3741 86 ± 8
Wu, 2017 [25] China Prospective cohort Hospital, ED Atrial fibrillation 1321 x ± x
Cheng, 2016 [57] USA Retrospective cohort Community None specific 4565 74 ± 5
Flodin, 2016 [26] Sweden Prospective cohort Hospital Hip fracture 843 82 ± 7
Calabia, 2015 [58] Spain Retrospective cohort Hospital, Nephrology Haemodialysis 3978 75 ± 6
Kim, 2015 [59] Korea Retrospective cohort Community Chronic diseases x x ± x
Kubota, 2015 [60] Japan Retrospective cohort Community T2DM 16,304 # x ± x
Kuo, 2015 [27] Taiwan Prospective cohort Outpatients T2DM x x ± x
Shil Hong, 2015 [61] Korea Retrospective cohort Community None specific 1000 76 ± 9
Buys, 2014 [28] USA Prospective cohort Community None specific 1257 75 ± 7
Clark, 2014 [62] USA/Nigeria Retrospective cohort Community None specific 2466 77 ± 5 *
Ford, 2014 [29] USA Prospective Cohort Community None specific 2995 81 ± 4
Lang, 2014 [30] France Prospective cohort Hospital, ED None specific 1306 85 ± 6
Lee, 2014 [31] Korea Prospective cohort Community None specific 11,844 73 ± 7
Murphy, 2014 [63] Iceland Retrospective cohort Community T2DM 637 77 [66–96] ♠
Wu, 2014 [32] Taiwan Prospective cohort Community None specific 77,541 73 ± 7
Yamauchi, 2014 [64] Japan Retrospective cohort Hospital, Pulmonology COPD 263,940 78 ± 7
Chen, 2013 [33] Taiwan Prospective cohort Veterans None specific 1257 83 ± 5
Dahl, 2013 [34] Sweden Prospective cohort Community None specific 882 80 ± 6
Nakazawa, 2013 [35] Japan Prospective cohort Nursing home None specific 8510 84 ± 8
Takata, 2013 [36] Japan Prospective cohort Community None specific 675 80 ± 0
Tseng, 2013 [37] Taiwan Prospective cohort Community T2DM 34,825 x ± x
Veronese, 2013 [38] Italy Prospective cohort Nursing home None specific 181 81 ± 8
Woo, 2013 [39] China Prospective cohort Community None specific 4000 73 ± 5
Yamamoto, 2013 [40] France Prospective cohort Hospital, Cardiology TAVI patients 3072 83 ± 7
Zekry, 2013 [41] Switzerland Prospective cohort Hospital, Geriatric None specific 444 85 ± 7
de Hollander, 2012 [42] Netherlands Prospective cohort Community None specific 1980 73 ± 2
Kvamme, 2012 [43] Norway Prospective cohort Community None specific 16,711 73 ± 5
Mihel, 2012 [44] Croatia Prospective cohort Community Hypertension 2507 x ± x
Tsai, 2012 [65] Taiwan Retrospective cohort Community None specific 2892 x ± x
Cereda, 2011 [45] Italy Prospective cohort LTCF None specific 533 84 ± 8
Berraho, 2010 [46] France Prospective cohort Community None specific 3646 75 ± 7
Han, 2010 [47] Korea Prospective cohort Community None specific 877 75 ± 8
Kitamura, 2010 [48] Japan Prospective cohort Home care None specific 205 84 ± 8
Lea, 2009 [66] USA Retrospective cohort Hospital, Cardiology AMI 74,167 77 ± x *
Luchsinger, 2008 [49] USA Prospective cohort Community None specific 1372 78 ± 6
Locher, 2007 [50] USA Prospective cohort Community None specific 983 75 ± 7
Takata, 2007 [51] Japan Prospective cohort Community None specific 697 80 ± 0
Grabowski, 2001 [67] USA Retrospective cohort Community None specific 7527 77 ± 6
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SD: Standard deviation; ICU: Intensive care unit; ED: Emergency department; TAVI: Transcatheter Aortic Valve Implementation; COPD: Chronic Obstructive Pulmonary Disease; AMI: Acute Myocardial Infarction; T2DM: Type 2 Diabetes Mellitus; LTCF: Long-term care facility. x: Missing information; #: Person-years; *: Pooled mean and/or standard deviation have been calculated with the information available in these articles; ♣: Median [range]; ♠: Mean [range].

As shown in Table 2, 20 of the 58 studies included in this review did not find any evidence of an obesity paradox [17,27,28,29,36,39,42,43,46,47,49,50,53,56,59,62,63,65,68,69]. Of these 20 studies, 16 involved patients with no specific medical condition [17,28,29,36,39,42,43,46,47,49,50,53,56,62,65,69]. One involved patients with chronic diseases [59], and two involved patients with type 2 diabetes mellitus [27,63]. Of the 58 studies, 34 used the threshold of BMI ≥ 25.0 kg/m2 [11,12,14,16,19,20,21,22,24,26,30,31,32,34,38,40,41,44,45,51,52,54,55,57,58,60,66,67,68]. A further 10 studies used a threshold different from 25 kg/m2 and found evidence of the obesity paradox [13,18,23,25,33,35,37,48,61,64]. Regarding the time points, 9 studies looked at short-term mortality (less than 12-month mortality, ICU mortality, hospital mortality) [11,12,19,30,40,52,55,64,68]. All of these, except Yamamoto et al. [40] and Kananen et al. [68], found evidence of the obesity paradox. Of the 28 studies that examined longer-term mortality (time point ≥ 5 years) [13,14,15,20,22,27,28,32,34,36,37,38,39,42,44,45,46,49,53,56,57,58,59,60,61,62,63,66,67], 15 (54%) found evidence of the obesity paradox [13,14,20,22,32,34,37,38,44,45,57,58,60,61,66,67]. In the studies that were conducted in people with a particular medical condition (n = 24) [11,12,14,16,18,19,21,24,25,26,27,37,40,44,52,54,55,58,59,60,63,64,66,68], the obesity paradox appeared in 18 (75%) cases [11,12,14,16,18,19,21,24,25,26,37,40,44,52,54,55,58,60,64,66]. In the studies that were carried out among people with no specific medical condition (n = 34) [13,15,17,20,22,23,28,29,30,31,32,33,34,35,36,38,39,41,42,43,45,46,47,48,49,50,51,53,56,57,61,62,65,67], the obesity paradox appeared in 17 (50%) cases [22,23,30,31,32,33,34,35,38,41,45,48,51,57,61,67].

Table 2.

Outcomes and association between body mass index group and mortality in aged adults.

Author(s), Year Age
(Mean ±
SD)		 Medical Condition Outcome Obesity Paradox BMI Thresholds # (kg/m2)
Kananen, 2022 [68] x ± x COVID-19 In-hospital mortality No 18.5 < BMI < 25.0
Amin, 2021 [11] x ± x Hip fracture 30-day mortality Yes BMI ≥ 25.0
(No, if BMI > 40.0)
Danninger, 2021 [52] x ± x Sepsis ICU mortality Yes BMI ≥ 30.0
El Moheb, 2021 [12] 75 ± x Emergent Surgery 30-day mortality Yes BMI ≥ 25.0
Lin, 2021 [13] 74 ± 6 None specific 84-month mortality Yes BMI ≥ 24.0
Martinez-Tapia, 2021 [14] 81 ± 6 Cancer 12-month mortality (men) Yes BMI ≥ 30.0
12-month mortality (women) No
60-month mortality (men) Yes BMI ≥ 30.0
60-month mortality (women) Yes BMI ≥ 30.0
Lai, 2020 [15] 79 ± 8 None specific 72-month mortality No
Schneider, 2020 [16] 72 ± x Glioblastoma 12-month mortality Yes BMI ≥ 30.0
Seino, 2020 [53] 72 ± 6 None specific All-cause mortality (men) No
All-cause mortality (women) No
Nishida, 2019 [17] 74 ± 5 None specific 36-month mortality No
Om, 2019 [18] 79 ± x Aortic stenosis 12-month mortality Yes BMI ≥ 24.9
Tokarek, 2019 [54] 82 ± x TAVI patients 12-month survival Yes BMI ≥ 30.0
Yoshihisa, 2019 [19] x ± x AHF In-hospital mortality Yes BMI ≥ 25.0
Crotti, 2018 [20] 72 ± 5 None specific 68-month mortality Yes BMI ≥ 25.0
(No, if BMI > 30.0)
68-month CVD mortality No
68-month cancer mortality No
De Palma, 2018 [21] 83 ± 6 TAVI patients 12-month mortality Yes BMI ≥ 25.0
50-month mortality Yes BMI ≥ 25.0
Keller, 2018 [55] 80 ± x AMI In-hospital mortality Yes BMI ≥ 30.0
Kim, 2018 [22] 72 ± 5 None specific 60-month mortality Yes BMI ≥ 25.0
(No, if BMI > 27.5)
Lee, 2018 [56] 72 ± 5 None specific 60-month mortality No
Lv, 2018 [23] 92 ± 8 None specific 36-month mortality Yes BMI ≥ 18.5
De Souto Barreto, 2017 [24] 86 ± 8 Dementia 18-month mortality (dementia) Yes BMI ≥ 25.0
18-month mortality (without dementia) Yes BMI ≥ 25.0
Wu, 2017 [25] x ± x Atrial fibrillation 12-month mortality (65–74 years) No
12-month mortality (≥75 years) Yes BMI ≥ 24.0
Cheng, 2016 [57] 74 ± 5 None specific 132-month mortality Yes BMI ≥ 25.0
(No, if BMI ≥ 35.0)
Diabetes Yes BMI ≥ 25.0
(No, if BMI ≥ 35.0)
Hypertension Yes BMI ≥ 25.0
(No, if BMI ≥ 35.0)
Dyslipidaemia Yes BMI ≥ 25.0
(No, if BMI ≥ 35.0)
Flodin, 2016 [26] 82 ± 7 Hip fracture 12-month survival Yes BMI > 26.0
Calabia, 2015 [58] 75 ± 6 Haemodialysis 120-month mortality Yes BMI = 30.0–34.9
(No, if BMI = 27.5–29.9 or BMI ≥ 35.0)
Kim, 2015 [59] x ± x Chronic diseases 108-month mortality No
Kubota, 2015 [60] x ± x T2DM 132-month ID mortality Yes BMI ≥ 25.0
Kuo, 2015 [27] x ± x T2DM 66-month mortality No
Shil hong, 2015 [61] 76 ± 9 None specific 72-month mortality Yes BMI ≥ 23.8
Buys, 2014 [28] 75 ± 7 None specific 102-month mortality No
Clark, 2014 [62] 77 ± 5 None specific 120-month mortality (Africans) No
120-month mortality (African Americans) No
Ford, 2014 [29] 81 ± 4 None specific 40-month mortality No
Lang, 2014 [30] 85 ± 6 None specific 6-week mortality Yes BMI ≥ 30.0
12-month mortality Yes BMI ≥ 25.0
24-month mortality Yes BMI ≥ 25.0
Lee, 2014 [31] 73 ± 7 None specific 36-month mortality Yes BMI ≥ 25.0
(No, if BMI ≥ 30.0)
Murphy, 2014 [63] 77 ± x T2DM 84-month mortality No
Wu, 2014 [32] 73 ± 7 None specific 60-month mortality Yes BMI ≥ 25.0
(No, if BMI ≥ 35.0)
60-month CVD mortality BMI ≥ 25.0
(No, if BMI ≥ 30.0)
Yamauchi, 2014 [64] 78 ± 7 COPD In-hospital mortality Yes BMI ≥ 23.0
Chen, 2013 [33] 83 ± 5 None specific 18-month mortality Yes BMI ≥ 23.0
Dahl, 2013 [34] 80 ± 6 None specific 216-month mortality Yes BMI ≥ 25.0
(No, if BMI ≥ 30.0)
Nakazawa, 2013 [35] 84 ± 8 None specific 12-month mortality Yes BMI ≥ 23.6
Takata, 2013 [36] 80 ± 0 None specific 144-month mortality No
144-month CVD mortality No
144-month cancer mortality No
Tseng, 2013 [37] x ± x T2DM 144-month mortality Yes BMI ≥ 23.0
Veronese, 2013 [38] 81 ± 8 None specific 60-month Yes BMI ≥ 30.0
Woo, 2013 [39] 73 ± 5 None specific 84-month mortality No
Yamamoto, 2013 [40] 83 ± 7 TAVI patients 30-day mortality No
12-month mortality Yes BMI ≥ 25.0
Zekry, 2013 [41] 85 ± 7 None specific 48-month mortality Yes BMI ≥ 30.0
de Hollander, 2012 [42] 73 ± 2 None specific 120-month mortality No
Kvamme, 2012 [43] 73 ± 5 None specific 12-month mortality (men) No
12-month mortality (women) No
Respiratory diseases 12-month mortality (men) No
12-month mortality (women) No
CVD 12-month mortality (men) No
12-month mortality (women) No
Cancer 12-month mortality (men) No
12-month mortality (women) No
Mihel, 2012 [44] x ± x Hypertension 60-month mortality (men) Yes BMI ≥ 30.0
60-month mortality (women) No
Tsai, 2012 [65] x ± x None specific 48-month mortality (65–74 y; men) No
48-month mortality (≥75 y; men) No
48-month mortality (65–74 y; women) No
48-month mortality (≥75 y; women) No
Cereda, 2011 [45] 84 ± 8 None specific 72-month mortality Yes BMI ≥ 25.0
Berraho, 2010 [46] 75 ± 7 None specific 156-month mortality No
Han, 2010 [47] 75 ± 8 None specific 42-month mortality No
Kitamura, 2010 [48] 84 ± 8 None specific 24-month mortality Yes BMI ≥ 17.1
Lea, 2009 [66] 77 ± x AMI 125-month mortality Yes BMI ≥ 25.0
(No, if BMI > 40.0)
Luchsinger, 2008 [49] 78 ± 6 None specific 144-month mortality No
Locher, 2007 [50] 75 ± 7 None specific 36-month mortality No
Takata, 2007 [51] 80 ± 0 None specific 48-month mortality Yes BMI ≥ 25.0
48-month CVD mortality No
48-month cancer mortality No
Grabowski, 2001 [67] 77 ± 6 None specific 96-month mortality Yes BMI ≥ 28.5
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# BMI thresholds at which an obesity paradox was demonstrated. SD: Standard deviation; ICU: Intensive Care Unit; TAVI: Transcatheter Aortic Valve Implementation; COPD: Chronic Obstructive Pulmonary Disease; AHF: Acute Heart Failure; AMI: Acute Myocardial Infarction; T2DM: Type 2 Diabetes Mellitus; CVD: Cardiovascular disease; y, years. x: Missing information.

An appendix provides detailed information of the analyses and results of the relationship between BMI and mortality in aged adults. Of the analyses tested for the existence of an obesity paradox, 48 were adjusted for confounders, and 10 were unadjusted analyses (see Supplementary Materials).

The quality of the included studies, as assessed using the NOS, was considered high for all 58 studies (Table 3).

Table 3.

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

Author, Year Study Design Selection Comparability Outcome Total Score Quality Rating
Kananen, 2022 [68] Retrospective cohort **** ** *** 9 High
Amin, 2021 [11] Prospective cohort **** ** *** 9 High
Danninger, 2021 [52] Retrospective cohort **** ** *** 9 High
El Moheb, 2021 [12] Prospective cohort **** ** *** 9 High
Lin, 2021 [13] Prospective cohort *** ** *** 8 High
Martinez-Tapia, 2021 [14] Prospective cohort **** ** *** 9 High
Lai, 2020 [15] Prospective cohort **** ** *** 9 High
Schneider, 2020 [16] Prospective cohort **** ** *** 9 High
Seino, 2020 [53] Retrospective cohort **** ** *** 9 High
Nishida, 2019 [17] Prospective cohort **** ** *** 9 High
Om, 2019 [18] Prospective cohort **** * *** 8 High
Tokarek, 2019 [54] Retrospective cohort **** * *** 8 High
Yoshihisa, 2019 [19] Prospective cohort **** * *** 8 High
Crotti, 2018 [20] Prospective cohort **** ** *** 9 High
De Palma, 2018 [21] Prospective cohort **** * *** 8 High
Keller, 2018 [55] Retrospective cohort **** * *** 8 High
Kim, 2018 [22] Prospective cohort **** ** *** 9 High
Lee, 2018 [56] Retrospective cohort **** ** *** 9 High
Lv, 2018 [23] Prospective cohort **** ** *** 9 High
de Souto Barreto, 2017 [24] Prospective cohort **** ** *** 9 High
Wu, 2017 [25] Prospective cohort **** ** *** 9 High
Cheng, 2016 [57] Retrospective cohort **** ** *** 9 High
Flodin, 2016 [26] Prospective cohort **** ** *** 9 High
Calabia, 2015 [58] Retrospective cohort **** ** *** 9 High
Kim, 2015 [59] Retrospective cohort **** ** *** 9 High
Kubota, 2015 [60] Retrospective study **** ** *** 9 High
Kuo, 2015 [27] Prospective cohort **** * *** 8 High
Shil Hong, 2015 [61] Retrospective cohort **** ** *** 9 High
Buys, 2014 [28] Prospective cohort *** ** *** 8 High
Clark, 2014 [62] Retrospective cohort **** ** *** 9 High
Ford, 2014 [29] Prospective cohort *** ** *** 8 High
Lang, 2014 [30] Prospective cohort **** ** *** 9 High
Lee, 2014 [31] Prospective cohort **** ** *** 9 High
Murphy, 2014 [63] Retrospective cohort **** ** *** 9 High
Wu, 2014 [32] Prospective cohort **** ** *** 9 High
Yamauchi, 2014 [64] Retrospective cohort **** ** *** 9 High
Chen, 2013 [33] Prospective cohort *** ** *** 8 High
Dahl, 2013 [34] Prospective cohort *** ** *** 8 High
Nakazawa, 2013 [35] Prospective cohort **** ** *** 9 High
Takata, 2013 [36] Prospective cohort *** ** *** 8 High
Tseng, 2013 [37] Prospective cohort **** ** *** 9 High
Veronese, 2013 [38] Prospective cohort *** ** *** 8 High
Woo, 2013 [39] Prospective cohort **** ** *** 9 High
Yamamoto, 2013 [40] Prospective cohort **** ** *** 9 High
Zekry, 2013 [41] Prospective cohort **** ** *** 9 High
de Hollander, 2012 [42] Prospective cohort *** ** *** 8 High
Kvamme, 2012 [43] Prospective cohort **** ** *** 9 High
Mihel, 2012 [44] Prospective cohort *** * *** 7 High
Tsai, 2012 [65] Retrospective cohort **** ** *** 9 High
Cereda, 2011 [45] Prospective cohort *** ** *** 8 High
Berraho, 2010 [46] Prospective cohort **** ** *** 9 High
Han, 2010 [47] Prospective cohort **** ** *** 9 High
Kitamura, 2010 [48] Prospective cohort **** ** *** 9 High
Lea, 2009 [66] Retrospective cohort **** ** *** 9 High
Luchsinger, 2008 [49] Prospective cohort **** ** *** 9 High
Locher, 2007 [50] Prospective cohort **** ** *** 9 High
Takata, 2007 [51] Prospective cohort **** ** *** 9 High
Grabowski, 2001 [67] Retrospective cohort **** ** *** 9 High
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Each star is equal to one point. The sum of the stars gives the total score of the NOS. NOS score of ≥7 were considered as high quality studies, NOS score of 5–6 as moderate quality, and NOS Scores less than 5 as low quality.

4. Discussion

In this systematic review of studies exploring the relationship between BMI and mortality in patients aged 65 years or older, 28 out of the 58 studies included observed longer survival in patients with a BMI ≥ 25 kg/m2 (the so-called obesity paradox) [11,12,14,16,19,20,21,22,24,26,30,31,32,34,38,40,41,44,45,51,52,54,55,57,58,60,66,67]. Among these 28 studies, 16 involved patients with a specific or acute medical condition [11,12,14,16,19,21,24,26,40,44,52,54,55,58,60,66]. Seven studies found improved survival in overweight and obese older people when focussing on short-term mortality [11,12,19,30,52,55,64,70]. One showed increased survival only in the oldest patients [25]. Two showed increased survival only in men [14,44]. Of the 23 studies that did not observe an obesity paradox [14,15,17,25,27,28,29,36,39,40,42,43,46,47,49,50,53,56,59,62,63,65,68], 7 involved populations selected according to the presence of a particular medical condition [14,25,27,40,59,63,68].

Nearly two-thirds of the studies included in this work report better survival in overweight or obese older people. Several factors may influence the relationship between obesity and survival in the older population, including age, degree of obesity, presence or absence of comorbidities, and occurrence of an acute event.

Regarding age, the studies in this review that failed to show better survival in overweight or obese individuals included populations that were, on average, younger than those demonstrating an obesity paradox. Wu et al. [25], in their study of the impact of age on the association between BMI and all-cause mortality in patients with atrial fibrillation, found better survival in overweight or obese patients aged 75 years or older but not in patients aged between 65 and 74 years. Observations made in older populations must therefore take into account the intrinsic characteristics of the survivors. For the same BMI, patient profiles can be different, and this profile can influence survival. For instance, body composition may differ due to ethnicity, sex, or advancing age [71,72]. BMI does not provide information on body composition, and is less correlated with percentage of body mass or fat mass index, especially in younger people [72]. Abdominal obesity has direct metabolic consequences (adipose tissue inflammation, dysglycaemia, alteration of blood pressure regulation, etc.). Conversely, subcutaneous fat accumulation in the hips, for example, appears to have benign effects on cardiovascular risk. Other indicators, such as waist circumference or waist-to-hip ratio, are strongly associated with higher mortality risk [73,74]. Taking only BMI into account does not make it possible to differentiate between these situations [9]. In all studies included in this work, BMI was defined as an obesity index. If obesity is defined by “body adiposity”, BMI level is probably not the best criterion [75]. The term “BMI paradox” may be more appropriate than “obesity paradox”, as suggested by Antonopoulos et al. [9].

Obesity is a factor associated with higher mortality in younger populations [76,77,78], but it is also associated with an increased risk of developing and dying from a number of diseases [3], such as cancer [79,80], Some authors point to the obesity-related cellular and immune changes that make obese people more vulnerable, including an increased risk of infections [1]. Older obese people could be considered constitutionally more robust as they have survived the risk factor of obesity into adulthood. The degree of obesity could also be a factor. In this review, not all authors differentiated between different classes of obesity. However, the positive effect on survival in cases of overweight and obesity was not found for morbid obesity (BMI ≥ 35.0 kg/m²) in 5 studies [11,32,57,58,66]. Furthermore, weight is not a reflection of body composition, in particular the muscle mass/fat mass ratio. Loss of muscle mass and strength (sarcopenia) is a factor associated with an increased risk of death. Tian et al. reported that obese people with sarcopenia have a higher risk of death than obese people without sarcopenia [81]. Obese people may be less frequently sarcopenic than non-obese people. In 1493 subjects aged 65 years or more (median age 74 ± 11 years), Sousa-Santos et al. [82] found a prevalence of 0.8% of obese sarcopenic individuals versus 11.6% of sarcopenic individuals of all BMI status.

The presence of a chronic pathology or an acute event may also influence survival. In this review, 20 studies [11,12,14,16,18,19,21,24,25,26,37,40,44,52,54,55,58,60,64,66] of the 38 which found a favourable effect of overweight or obesity on survival involved patients with a particular chronic condition or facing a specific medical event. This finding suggests that even moderately overweight older individuals with chronic disease or acute medical events have better survival. Obesity in older people with a chronic disease could be a sign of greater robustness or higher reserves (better appetite, less risk of undernutrition). Overweight or obese older subjects would be less undernourished than the general older population. Cereda et al. [83], in their meta-analysis of the prevalence of undernutrition in an older population, found a prevalence of undernutrition ranging from 3.1 to 29.4%, depending on the setting. Sousa-Santos et al. [84] showed that 6% of obese elderly subjects (BMI ≥ 30 kg/m2) were also undernourished or at risk of undernutrition. In the event of an acute event, obese elderly people may have a better chance of survival, particularly because of their greater functional reserves. This observation is also made in younger obese or overweight subjects. Akinnusi et al. [85] show in their meta-analysis of patients admitted to intensive care that obese subjects have a similar mortality to non-obese subjects. In 2013, the meta-analysis by Flegal et al. [76] confirmed in a population without any particular pathology that overweight people (BMI > 25 kg/m²) (all types of obesity and all ages) had a higher overall mortality rate, whatever the cause. However, mildly overweight people (BMI ≥ 25 and <30 kg/m²) had lower all-cause mortality than normal weight people (BMI < 25 kg/m²). Thus, this advantage was found regardless of age.

Several mechanisms could explain “obesity paradox”. Probably, there are “good adipose tissues” in elderly subjects. In the literature, overweight or obesity, defined by high level of BMI, is shown to have positive influence on prothrombotic factors, production of certain cytokines, or NT-proBNP levels. Adipokine produced by adipose tissue seems to be cardioprotective [86]. Obesity could have a protective effect against progression or consequences of some chronic diseases. High BMI could also reflect better nutritional status and adequate muscle reserves. Casas-Vara et al. [87] showed better nutritional status in overweight or obese elderly people with heart failure.

Our systematic review has limitations. Although the WHO has proposed thresholds for BMI, the authors used different thresholds in their respective studies. In addition, the outcomes were also different between the studies. This made it difficult to compare the studies, and precluded meta-analysis. The age variable was missing in 14.0% of cases (8/57).

However, this work covers a large number of studies, totalling more than 1,120,000 people aged 65 years or over, with varying medical conditions and in different settings. The follow-up time of the studies ranged from 30 days to 156 months (even though the majority of studies have a long-term follow-up). These differences in follow-up time may make comparison difficult. In addition, there is no information on BMI variation over time, especially for studies with long-term follow-up. Weight loss or gain between baseline measurement and death could have a significant impact. The fact that only studies conducted in subjects aged 65 years or older were selected gives a certain homogeneity to this systematic review in terms of population. Finally, all studies were evaluated for methodological quality using the NOS, and were found to be of high quality.

5. Conclusions

The findings of this systematic review are in favour of the existence of an obesity paradox, which could more specifically concern older subjects with a comorbidity and/or experiencing an acute event. Nevertheless, because BMI does not reflect body composition, the term “BMI paradox” would be more appropriate. The influence of the level of BMI remains unclear. These findings should help guide strategies for nutritional counselling in the older population.

Acknowledgments

Thanks to Fiona Ecarnot for editorial assistance.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/nu15071780/s1, Table S1: Outcome and results of association between body mass index groups and mortality in aged adults (detailed information).

Click here for additional data file. (67.2KB, zip)

Author Contributions

L.G. and M.D. conceived and designed the study, prepared the material, collected the data, and performed the analysis. They wrote the first draft of the manuscript, and approved the final manuscript. All authors have read and agreed to the published version of the manuscript.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data could be made available on reasonable request at moustapha.drame@chu-martinique.fr.

Conflicts of Interest

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Funding Statement

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. The APC was funded by tht University Hospitals of Martinique.

Footnotes

Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

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Data Availability Statement

Data could be made available on reasonable request at moustapha.drame@chu-martinique.fr.

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