Effect of obesity on intensive care morbidity and mortality: a meta-analysis. Crit Care Med

Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, Western New York Respiratory Research Center, University at Buffalo School of Medicine and Biomedical Sciences, Buffalo, NY, USA.
Critical care medicine (Impact Factor: 6.31). 01/2008; 36(1):151-8. DOI: 10.1097/01.CCM.0000297885.60037.6E
Source: PubMed
ABSTRACT
To evaluate the effect of obesity on intensive care unit mortality, duration of mechanical ventilation, and intensive care unit length of stay among critically ill medical and surgical patients.
Meta-analysis of studies comparing outcomes in obese (body mass index of > or = 30 kg/m2) and nonobese (body mass index of < 30 kg/m2) critically ill patients in intensive care settings.
MEDLINE, BIOSIS Previews, PubMed, Cochrane library, citation review of relevant primary and review articles, and contact with expert informants.
Not applicable.
A total of 62,045 critically ill subjects.
Descriptive and outcome data regarding intensive care unit mortality and morbidity were extracted by two independent reviewers, according to predetermined criteria. Data were analyzed using a random-effects model.
Fourteen studies met inclusion criteria, with 15,347 obese patients representing 25% of the pooled study population. Data analysis revealed that obesity was not associated with an increased risk of intensive care unit mortality (relative risk, 1.00; 95% confidence interval, 0.86-1.16; p = .97). However, duration of mechanical ventilation and intensive care unit length of stay were significantly longer in the obese group by 1.48 days (95% confidence interval, 0.07-2.89; p = .04) and 1.08 days (95% confidence interval, 0.27-1.88; p = .009), respectively, compared with the nonobese group. In a subgroup analysis, an improved survival was observed in obese patients with body mass index ranging between 30 and 39.9 kg/m2 compared with nonobese patients (relative risk, 0.86; 95% confidence interval, 0.81-0.91; p < .001).
Obesity in critically ill patients is not associated with excess mortality but is significantly related to prolonged duration of mechanical ventilation and intensive care unit length of stay. Future studies should target this population for intervention studies to reduce their greater resource utilization.

Full-text

Available from: Ali El Solh, Jul 26, 2014
Effect of obesity on intensive care morbidity and mortality:
A meta-analysis*
Morohunfolu E. Akinnusi, MD; Lilibeth A. Pineda, MD; Ali A. El Solh, MD, MPH
O
besity is a chronic disease
and a major health problem
due to its causal relationship
with serious medical dis-
eases, increased morbidity and mortality,
and substantial economic effect. Accord-
ing to the World Health Organization,
the prevalence of obesity has been
steadily increasing worldwide (1, 2). The
estimated mortality attributable to obe-
sity alone among U.S. adults is approxi-
mately 300,000 annually (3), and the di-
rect costs associated with this disease are
reported to represent 5.7% of the Na-
tional Health expenditure in the United
States (4).
Obesity is characterized by a series of
physiologic changes that may impair the
ability to adapt to the stresses of critical
illness. The presence of diabetes, cardio-
vascular strains, and respiratory dysfunc-
tion poses significant challenges that may
affect intensive care unit (ICU) survival.
However, the influence of obesity on out-
comes among critically ill patients re-
mains a focus on controversy. Some stud-
ies looking at ICU outcome and obesity
showed increased mortality and morbid-
ity (5–11), whereas others showed either
a decrease (12–17) or no association (18
22). Because of the heterogeneity among
these studies, we performed a meta-
analysis of published studies to investi-
gate the association between obesity and
ICU outcome and to determine whether
there is a dose-response effect of elevated
body mass index (BMI) on ICU mortality.
MATERIALS AND METHODS
Search Strategy. This study was conducted
according to the checklist of the Meta-analysis
of Observational Studies in Epidemiology
(MOOSE) group (23). We searched MEDLINE
(1966 to February 2007), BIOSIS Previews
(1990 to February 2007), PubMed (mid 1960s
to February 2007), Embase (January 1990 to
February 2007), and Cochrane Library, with-
out any language restriction, using relevant
text words and search terms to identify articles
containing at least one of the following key
words: obesity, body mass index, mortality,
intensive care unit, or trauma. Close scrutiny
and hand searches through cited references of
identified articles were undertaken. Abstracts
of conference proceedings from meetings of
relevant medical societies were perused, and
we communicated electronically with some
listed authors of studies reviewed, for clarifi-
cation and retrieval of reported and unre-
ported but presumed relevant data. The Insti-
tutional Review Board has waived the need for
approval or informed consent.
Study Selection and Data Extraction. In-
clusion criteria were studies comparing obese
with nonobese critically ill patients admitted
to an ICU. Obesity was defined according to
*See also p. 369.
From the Division of Pulmonary, Critical Care, and
Sleep Medicine, Department of Medicine, Western
New York Respiratory Research Center, University at
Buffalo School of Medicine and Biomedical Sciences,
Buffalo, NY.
The authors have not disclosed any potential con-
flicts of interest.
Supported, in part, by Research for Health in Erie
County, Buffalo, NY.
For information regarding this article, E-mail:
solh@buffalo.edu
Copyright © 2007 by the Society of Critical Care
Medicine and Lippincott Williams & Wilkins
DOI: 10.1097/01.CCM.0000297885.60037.6E
Objective: To evaluate the effect of obesity on intensive care
unit mortality, duration of mechanical ventilation, and intensive
care unit length of stay among critically ill medical and surgical
patients.
Design: Meta-analysis of studies comparing outcomes in
obese (body mass index of >30 kg/m
2
) and nonobese (body mass
index of <30 kg/m
2
) critically ill patients in intensive care set-
tings.
Data Source: MEDLINE, BIOSIS Previews, PubMed, Cochrane
library, citation review of relevant primary and review articles,
and contact with expert informants.
Setting: Not applicable.
Patients: A total of 62,045 critically ill subjects.
Interventions: Descriptive and outcome data regarding inten-
sive care unit mortality and morbidity were extracted by two
independent reviewers, according to predetermined criteria. Data
were analyzed using a random-effects model.
Measurements and Main Results: Fourteen studies met inclu-
sion criteria, with 15,347 obese patients representing 25% of the
pooled study population. Data analysis revealed that obesity was
not associated with an increased risk of intensive care unit
mortality (relative risk, 1.00; 95% confidence interval, 0.86 –1.16;
p .97). However, duration of mechanical ventilation and inten-
sive care unit length of stay were significantly longer in the obese
group by 1.48 days (95% confidence interval, 0.07–2.89; p .04)
and 1.08 days (95% confidence interval, 0.27–1.88; p .009),
respectively, compared with the nonobese group. In a subgroup
analysis, an improved survival was observed in obese patients
with body mass index ranging between 30 and 39.9 kg/m
2
com-
pared with nonobese patients (relative risk, 0.86; 95% confidence
interval, 0.81– 0.91; p < .001).
Conclusion: Obesity in critically ill patients is not associated
with excess mortality but is significantly related to prolonged
duration of mechanical ventilation and intensive care unit length
of stay. Future studies should target this population for interven-
tion studies to reduce their greater resource utilization. (Crit Care
Med 2008; 36:151–158)
K
EY WORDS: intensive care unit; obesity; body mass index;
mortality; length of stay; mechanical ventilation
151Crit Care Med 2008 Vol. 36, No. 1
Page 1
the National Heart, Blood, and Lung Insti-
tute’s (NHBLI) published guidelines (24)
based on BMI. We excluded noncomparative
studies and studies conducted outside an ICU
setting. We excluded also studies that utilized
the same patient population, including only
the study with the most number of patients
from the same data set.
The primary outcome was ICU mortality.
ICU length of stay (LOS) and duration of me-
chanical ventilation were included as second-
ary outcomes when available. We contacted
authors of the primary articles with missing
data as necessary.
Study Quality. Two reviewers indepen-
dently rated each study’s quality. Because
there are no validated tools for quality assess-
ment of outcome studies, we adapted the McMaster
criteria for evaluating the validity of studies
about prognosis (25). Studies were assessed
for presence of five features: description of
patient sample characteristics, description of
inclusion and exclusion criteria, potential se-
lection bias, definition of outcomes at the start
of the study, and objectivity of outcomes. The
intraclass correlation coefficient for agree-
ment between the two raters on overall quality
rating for all included studies was 0.85. Dis-
agreements were resolved by consensus.
Data Synthesis and Statistical Analysis.
Data extracted from the selected studies in-
cluded: 1) the total number of obese (BMI 30
kg/m
2
) and nonobese patients (BMI 30 kg/m
2
)
in each study, 2) mortality rate, 3) ICU LOS, and
4) duration of mechanical ventilation. Data were
analyzed for the various BMI classes whenever
reported by investigators. In studies in which
only a range for LOS or duration of mechanical
ventilation was reported, we calculated estimates
of the
SD using the Hurlburt’s range method (26)
to ensure uniformity of data recording.
Meta-analysis was performed using Rev-
man 4.2.9 (Cochrane collaboration, Oxford,
UK). Data were pooled using the random-
effects model of DerSimonian and Laird (27)
to account for both within-study and between-
study variations. The pooled effect estimate for
ICU mortality was expressed as relative risk
(RR) with 95% confidence intervals (CIs),
whereas LOS and duration of mechanical ven-
tilation were expressed as mean differences
with 95% CIs. Differences in outcomes esti-
mates between the obese and nonobese groups
were tested using a two-sided z test with sta-
tistical significance set at p .05.
We compared RR estimates of mortality for
all subgroups of patients using a two sided z
test on the log RRs and expressed as ratio of
RRs with its 95% CI. We also derived a curvi-
linear relationship using a polynomial distri-
bution between BMI strata and RR of mortality
(S-Plus 6.1, Insightful Co, Seattle, WA).
Statistical heterogeneity for all variables
was assessed by using the I
2
measure (28). To
evaluate for potential publication bias, we con-
structed a funnel plot for the primary out-
come, and we carried out the Begg’s rank
correlation tests as previously reported (29).
RESULTS
The iterative literature search initially
retrieved 29 potential relevant studies.
Using the prespecified inclusion criteria,
an abstract review rejected six references
(19, 20, 30 –33), yielding 23 studies can-
didate for possible inclusion in the meta-
analysis. Nine studies were subsequently
eliminated after a full article review (6,
12, 34 –39, 40). Fourteen studies met el-
igibility criteria established a priori
(Table 1). Figure 1 depicts our literature
search and study selection process. Seven
studies were prospective and seven were
retrospective in design. Eight studies (10,
13–15, 17, 18, 21, 22) stratified outcomes
based on BMI categories of 18.5, 18.5–
24.9, 25–29.9, 30–34.9, 35–39.9, and 40
kg/m
2
.
Figure 1. Flow diagram of literature search and study selection process. ICU, intensive care unit; BMI,
body mass index.
Table 1. Characteristics of studies included in the meta-analysis
First Author (Reference No.) Year Study Design
No. of Obese/Total
Patients (%) Study Population
Obesity Associated
with Mortality
El Solh et al. (5) 2001 Retrospective 117/249 (47) MICU Y
Bochicchio et al. (11) 2006 Prospective 62/1167 (5) Trauma ICU Y
Nasraway et al. (10) 2006 Retrospective 366/1373 (27) SICU Y
Brown et al. (9) 2005 Retrospective 283/1153 (25) Trauma ICU Y
Bercault et al. (7) 2004 Prospective 170/340 (50) MICU/SICU Y
Neville et al. (8) 2004 Retrospective 63/242 (26) Trauma ICU Y
Aldawood et al. (17) 2007 Prospective 540/1835 (29) Mixed ICU N
Peake et al. (21) 2006 Prospective 129/433 (30) MICU/SICU N
Alban et al. (15) 2006 Retrospective 135/918 (15) Trauma ICU N
O’Brien et al. (16) 2006 Retrospective 457/1488 (31) Mixed ICU N
Garrouste-Orgeas et al. (13) 2003 Prospective 227/1698 (13) Mixed ICU N
Ray et al. (18) 2005 Prospective 550/2148 (26) MICU N
Morris et al. (22) 2007 Prospective 237/825 (29) MICU N
Marik et al. (14) 2003 Retrospective 12011/48176 (25) Mixed ICU N
MICU, medical intensive care unit; Y, yes; N, no; ICU, intensive care unit; SICU, surgical intensive care unit.
152 Crit Care Med 2008 Vol. 36, No. 1
Page 2
Overall quality ratings ranged from 2
to 5 (Table 2). Common quality problems
included inadequately clear inclusion and
exclusion criteria in nine studies, poten-
tial selection bias in eight studies, and
problems with definition of outcomes at
the start of the study in two studies.
A total of 62,045 unique subjects were
included in the analysis. Of these, 15,347
were obese (BMI 30 kg/m
2
) and 46,698
were nonobese (BMI 30 kg/m
2
). Study
populations included were well-character-
ized cohorts in the United States, Europe,
Australia, and the Middle East. All patients
were admitted to either a medical, surgical,
or a mixed medical-surgical ICU. Table 1
illustrates the characteristics of the selected
studies. The patients ranged in age from 40
1.4 yrs to 65 14 yrs. Indications for
admission to the medical ICU varied
widely, the most common being respira-
tory disorders: pneumonia, unspecified
respiratory failure, and acute respiratory
distress syndrome. Surgical ICU admis-
sions were predominantly trauma-related
cases. In the selected studies, severity of
illness scores (Acute Physiology and
Chronic Health Evaluation II [range, 18
0.8 to 20.6 12.2], Simplified Acute
Physiology Score II [30.2 17.9 to 43
14], and Injury Severity Scores [21 12
to 24.8 12]) were comparable between
the obese (BMI 30 kg/m
2
) and nonobese
groups (BMI 30 kg/m
2
).
Overall Mortality. ICU mortality data
for obese (BMI 30 kg/m
2
) and nonobese
patients (BMI 30 kg/m
2
) were reported
in all selected studies. There were 1,749
(11.4%) and 5,891 (12.6%) primary end-
point events (mortality) in the two
groups, respectively. Pooled analysis of
data from these 14 studies revealed no
mortality difference between the obese and
the nonobese group (RR, 1.00; 95% CI,
0.86 –1.16; p .97; I
2
75.6%) (
Fig. 2).
However, the obese group had a higher
survival rate than the nonobese group (RR,
0.83; 95% CI, 0.74 0.92; p .001) at time
of hospital discharge (Fig. 3).
Duration of Mechanical Ventilation.
Six studies reported on duration of me-
chanical ventilation (5, 9, 11, 17, 18, 22).
The mean duration of mechanical venti-
lation in the obese group (BMI 30 kg/
Table 2. Quality ratings of included studies
Study, Authors
(Reference No.)
Description of
Patient Sample
Characteristics
Description of
Inclusion/Exclusion
Criteria
Potential
Selection Bias
Definition of
Outcomes at the
Start of the Study
Objectivity
of Outcomes Total
Alban et al. (15) 1 1 1 0 1 4
Aldawood et al. (17) 1 1 1 1 1 5
Bercault et al. (7) 1 1 0 1 1 4
Bochicchio et al. (11) 1 0 0 1 1 3
Brown et al. (9) 0 0 0 1 1 2
Garrouste-Orgeas et al. (13) 1 0 0 0 1 2
El Solh et al. (5) 1 1 1 1 1 5
Marik et al. (14) 1 0 1 1 1 4
Morris et al. (22) 1 0 1 1 1 4
Nasraway et al. (10) 1 0 0 1 1 3
Neville et al. (8) 1 0 1 1 1 4
O’Brien et al. (16) 1 0 1 1 1 4
Peake et al. (21) 0 0 1 1 1 3
Ray et al. (18) 1 1 0 1 1 4
1, listed; 0, not listed.
Figure 2. Forest plot examining the risk of intensive care unit mortality among obese vs. nonobese critically ill patients. Horizontal lines represent 95%
confidence intervals (CI); RR, relative risk.
153Crit Care Med 2008 Vol. 36, No. 1
Page 3
m
2
) ranged from 5.2 to 16.0 days com
-
pared with 4.6 to 9.4 days in the nonobese
group (BMI 30 kg/m
2
). The combined
mean difference in duration of mechani-
cal ventilation was lower by 1.48 days
(95% CI, 0.07–2.89; p .04; I
2
80.1%)
in the nonobese compared with the obese
group (Fig. 4).
Length of Stay in the Intensive Care
Unit. Thirteen studies contributed to the
analysis of ICU LOS data (5, 8 –11, 13–18,
21, 22). The mean LOS ranged from 2.1 to
19.4 days in the obese group (BMI 30
kg/m
2
) compared with 2.6 to 12.0 days in
the nonobese group (BMI 30 kg/m
2
). The
combined mean difference in ICU LOS was
lower by 1.08 (95% CI, 0.27–1.88; p .009;
I
2
98.8%) in the nonobese compared
with the obese group (Fig. 5).
Subgroup Analysis. Because of signif-
icant heterogeneity, we conducted
pooled analysis of studies that stratified
patients based on different categories of
BMI (Fig. 6). The analysis revealed no
Figure 3. Forest plot examining the risk of hospital mortality among obese vs. nonobese critically ill patients. Horizontal lines represent 95% confidence
intervals (CI). RCT, randomized controlled trial; RR, relative risk.
Figure 4. Forest plot depicting the association between obesity and duration of mechanical ventilation (MVD). Horizontal lines represent 95% confidence
intervals (CI). MVD, days of mechanical ventilation. WMD, weighted mean difference.
Figure 5. Forest plot depicting the association between obesity and intensive care unit length of stay (LOS). Horizontal lines represent 95% confidence
intervals (CI). WMD, weighted mean difference.
154 Crit Care Med 2008 Vol. 36, No. 1
Page 4
statistically significant difference in
ICU mortality between nonobese (BMI
30 kg/m
2
) and morbidly obese pa
-
tients (BMI 40 kg/m
2
) (RR, 0.97; 95%
CI, 0.74 –1.26; p .8; I
2
53.8%) (
Fig.
7). However there was a survival advan-
tage for the obese patients in the BMI
range of 30 –39.9 kg/m
2
over the nono
-
bese (RR, 0.86; 95% CI, 0.81– 0.91; p
.001; I
2
0) (
Fig. 8).
Publication Bias. Visual inspection of
the funnel plot for ICU mortality denotes
asymmetry, indicating underpublication of
negative results (Fig. 9). However, formal
statistical test using Begg’s rank correla-
tion did not support the presence of publi-
cation bias (Kendall’s with continuity cor-
rection, 0.18; one-tailed p .4).
DISCUSSION
There are currently no reported aggre-
gate data from ICUs about the proportion
of critically ill patients stratified by BMI
category. Although a number of clinical
investigations reported that obesity con-
tributes to increased ICU mortality, there
are other data describing a U-shaped as-
sociation, with excess mortality in pa-
tients who are underweight and in those
with severe obesity (41). These conflict-
ing conclusions are the byproducts of
clinical and methodologic heterogene-
ities stemming from variability in partic-
ipants and outcomes and from trial de-
sign and quality. It would not be
surprising, therefore, to find that the re-
sults of these trials were to some degree
Figure 6. Relative risk of mortality stratified according to body mass index (BMI) (95% confidence
interval). We obtained the risk trend (continuous line) and its 95% confidence band (dotted line)by
using a polynomial distribution.
Figure 7. Forest plot examining the risk of mortality among nonobese (body mass index of 30 kg/m
2
) vs. morbidly obese (body mass index of 40 kg/m
2
).
Horizontal lines represent 95% confidence interval (CI). RR, relative risk.
Figure 8. Forest plot examining the risk of mortality among nonobese (body mass index [BMI]of30 kg/m
2
) vs. obese with BMI of 30 –39.9 kg/m
2
.
Horizontal lines represent 95% confidence interval (CI). RR, relative risk.
155Crit Care Med 2008 Vol. 36, No. 1
Page 5
incompatible with one another. Indeed,
the I
2
test indicated significant degrees of
heterogeneity among the selected stud-
ies. It has been argued that a meta-
analysis should only be considered when
a group of trials is sufficiently homoge-
neous. However heterogeneity will always
exist in a meta-analysis, irrespective of
whether we are able to detect it using a
statistical test (28).
Obesity influences a variety of organ
systems, altering the expected physio-
logic response to injury and illness. The
extra burden placed on cardiovascular
function and respiratory mechanics has
been suspected to confer on obese pa-
tients a survival disadvantage when chal-
lenged with severe illness. In addition,
the distribution, metabolism, protein
binding, and clearance of many drugs are
altered in the obese, which usually result
in underdosing of critical therapeutic
agents. Hence, it was not surprising that
several studies (5–11) reported a worse
outcome in this subset of the population.
The most recent investigations, however,
seem to suggest that this trend has re-
versed and others insist that the correla-
tion does not exist (14, 16, 19, 22). Sev-
eral theories have been advanced to
explain this discrepancy. Physiologically,
it is plausible that access to the abun-
dant adipose tissue during the highly
catabolic state helps to prevent the
long-term complications associated
with critical illness. There are no clin-
ical data, however, to support this no-
tion at present, but there is increasing
evidence that adipocytes-secreting hor-
mones—leptin and interleukin-10
have immunomodulatory properties
that might curb the inflammatory re-
sponse and improve host survival in
response to severe illness. Leptin has a
notable regulatory effect on T-lympho-
cytes and interferon- production (42).
Animal studies have shown that leptin-
deficient mice exhibit an impaired host
response against Gram-negative pneu-
monia in vivo, and this defect was as-
sociated with impaired macrophage and
neutrophil phagocytosis of Klebsiella
pneumoniae and reduced macrophage
leukotriene synthesis in vitro (43, 44).
Clinical studies in humans have also
reported higher leptin levels in survi-
vors of severe sepsis and septic shock
than nonsurvivors (45). Interleukin-10
is another adipokine that possesses anti-
inflammatory properties that help con-
trol the initial inflammatory response in
critical illness by inhibiting the release of
proinflammatory cytokines such as tu-
mor necrosis factor, interleukin-6, and
interleukin-8 from macrophages (46).
Could it be that adipokines modulation of
inflammatory cytokines mitigate the
physiologic burden of obesity? A recent
investigation in murine model of pulmo-
nary infection suggests that shifting the
balance between proinflammatory and
anti-inflammatory mediators in favor of
the latter by interleukin-10 gene delivery
was able to restore normal diaphragmatic
force-generating capacity under these
conditions (47).
An alternative explanation for the lack
of difference in the odds of mortality
among critically ill obese and nonobese
patients is the increased clinical attention
that is being paid to the care of obese
patients following the early reports of de-
creased survival. In addition, the prolifer-
ation of therapeutic guidelines in the past
few years standardizing the management
of hyperglycemia and sepsis could have
potentially contributed to a significant
decline in the ICU complications of crit-
ically ill obese patients compared with
the nonobese, yielding effectively a com-
parable mortality rate between the two
groups.
In-hospital mortality findings from
our meta-analysis may not be at variance
with currently available data in the obe-
sity literature. This is underscored by re-
cent evidence suggesting that the rela-
tionship between obesity and hospital
mortality is a rather complex one. The
obesity paradox was reported in a study of
108,927 patients with acute decompen-
sated heart failure with in-hospital mor-
tality rates of 6.3%, 4.6%, 3.4%, and 2.4%
for underweight, healthy weight, over-
weight, and obese patients, respectively
(48). This finding may be explained partly
by the effect of chronically ill patients
constituting a large proportion of the
nonobese group. Similar findings were
shown in other studies (16, 49, 50).
Lastly, our literature search was directed
at studies that primarily addressed ICU
mortality. Our analysis of hospital mor-
tality was an extrapolated derivative.
Therefore we may have underestimated
the effect of excluded data from studies
primarily geared toward hospital out-
come in obese patients.
One consistent finding across the ma-
jority of the combined studies is the
longer duration of mechanical ventilation
and prolonged ICU length of stay in obese
patients compared with nonobese. Only
three of 13 studies that reported LOS data
failed to show this feature (8, 10, 17).
None of the studies showed a shorter
duration of mechanical ventilation in
obese patients compared with nonobese
patients. Duration of mechanical ventila-
tion was at best similar, in two studies
(17–18). The mechanical properties of
the total respiratory system, the lung,
and the chest wall of morbidly obese pa-
tients are characterized by marked de-
rangements compared with normal
weight subjects (51). Morbidly obese pa-
tients dedicate a disproportionately high
percentage of total body oxygen con-
sumption to conduct respiratory work,
even during quiet breathing. This relative
inefficiency suggests a decreased ventila-
tory reserve and a predisposition to respi-
ratory failure in the setting of even mild
pulmonary or systemic insults (52).
Moreover, the increase in perioperative
complications, particularly wound prob-
lems, explains our finding of a longer
LOS in postoperative obese patients (40).
Figure 9. Funnel plot assessing publication bias. The broken line represents the combined result of all
trials. ICU, intensive care unit. SE (log OR), standard error (logarithm of odds ratio); OR (fixed), odds
ratio according to “fixed effect model.”
156 Crit Care Med 2008 Vol. 36, No. 1
Page 6
Our meta-analysis has several key lim-
itations. First, the vast majority of studies
that have addressed the question of obe-
sity and mortality in the ICU are retro-
spective by design (5, 8 –10, 15–16, 34,
37, 39). As such, we cannot confidently
exclude the error of selection bias. Sec-
ond, because this study was based on
published reports rather than primary
data analysis, the ability to identify patient
characteristics associated with greater risks
was limited. Different groups of studies re-
ported on similar outcomes, yet each risk
estimate may have reflected differences in
true effects or biases particular to the stud-
ies from which the risk estimate was de-
rived. Third, as the global obesity epidemic
continues to amplify and spread, further
data will be required on mortality and mor-
bidity for those who are super-obese (BMI
50 kg/m
2
).
CONCLUSIONS
This meta-analysis suggests that al-
though mild and moderate obesity may
be protective during critical illness, mor-
bid obesity did not have an adverse effect
on outcome. However obese patients do
have increased morbidity as measured by
duration of mechanical ventilation and
LOS. As the waistline of the U.S. popula-
tion continues to enlargen, longer LOS
might have significant implications for
healthcare costs. Interventional studies
are needed to address the causes of and to
reduce the greater resource utilization.
ACKNOWLEDGMENT
We thank Dr. Brydon Grant for statis-
tical review of the manuscript.
REFERENCES
1. World Health Organization: Global strategy on
diet, physical activity and health. Available at:
http: // www.who.int / dietphysicalactivity /
publications/facts/obesity/en/. Accessed Febru-
ary 26, 2007
2. Ogden CL, Carroll MD, Curtin RL, et al:
Prevalence of overweight and obesity in the
United States, 1999 –2004. JAMA 2006; 295:
1549 –1555
3. Allison DB, Fontaine KR, Manson JE, et al:
Annual deaths attributable to obesity in the
United States. JAMA 1999; 282:1530 –1538
4. Wolf AM, Colditz GA: Current estimates of
the economic cost of obesity in the United
States. Obes Res 1998; 6:97–106
5. El Solh AA, Sikka P, Bozkanat E, et al: Mor-
bid obesity in the medical ICU. Chest 2001;
120:1989 –1997
6. Goulenok C, Monchi M, Chiche JD, et al:
Influence of overweight on ICU mortality: A
prospective study. Chest 2004; 125:
1441–1445
7. Bercault N, Boulain T, Kuteifan K, et al:
Obesity-related excess mortality rate in an
adult intensive care unit: A risk-adjusted
matched cohort study. Crit Care Med 2004;
32:998 –1003
8. Neville AL, Brown CV, Weng J, et al: Obesity
is an independent risk factor of mortality in
severely injured blunt trauma patients. Arch
Surg 2004; 139:983–987
9. Brown CV, Neville AL, Rhee P, et al: The
impact of obesity on the outcomes of 1,153
critically injured blunt trauma patients.
J Trauma 2005; 59:1048 –1051
10. Nasraway SA, Albert M, Donnelly AM, et al:
Morbid obesity is an independent determi-
nant of death among surgical critically ill
patients. Crit Care Med 2006; 34:964 –971
11. Bochicchio GV, Joshi M, Bochicchio K, et al:
Impact of obesity in the critically ill trauma
patient: A prospective study. J Am Coll Surg
2006; 203:533–538
12. Tremblay A, Bandi V: Impact of body mass
index on outcomes following critical care.
Chest 2003; 123:1202–1207
13. Garrouste-Orgeas M, Troche G, Azoulay E, et
al: Body mass index: An additional prognostic
factor in ICU patients. Intensive Care Med
2004; 30:437– 443
14. Marik PE, Doyle H, Varon J: Is obesity pro-
tective during critical illness? An analysis of a
national ICU database. Crit Care Shock 2003;
6:127–133
15. Alban RF, Lyass S, Margulies DR, et al: Obe-
sity does not affect mortality after trauma.
Am Surg 2006; 72:966 –969
16. O’Brien JM, Phillips GS, Ali NA, et al: Body
mass index is independently associated with
hospital mortality in mechanically ventilated
adults with acute lung injury. Crit Care Med
2006; 34:738 –744
17. Aldawood A, Arabi Y, Dabbagh O: Association
of obesity with increased mortality in the
critically ill patient. Anaesth Intensive Care
2006; 34:629 633
18. Ray DE, Matchett SC, Baker K, et al: The
effect of body mass index on patient out-
comes in a medical ICU. Chest 2005; 127:
2125–2131
19. O’Brien JM, Welsh CH, Fish RH, et al: Excess
body weight is not independently associated
with outcome in mechanically ventilated pa-
tients with acute lung injury. Ann Intern
Med 2004; 140:338 –345
20. Galanos AN, Pieper CF, Kussin PS, et al:
Relationship of body mass index to subse-
quent mortality among seriously ill hospital-
ized patients. Crit Care Med 1997; 25:
1962–1968
21. Peake SL, Moran JL, Ghelani DR, et al: The
effect of obesity on 12-month survival follow-
ing admission to intensive care: A prospec-
tive study. Crit Care Med 2006; 34:
2929 –2939
22. Morris AE, Stapleton RD, Rubenfeld GD, et
al: The association between body mass index
and clinical outcomes in acute lung injury.
Chest 2007; 131:342–348
23. Stroup DF, Berlin JA, Morton SC, et al: Meta-
analysis of observational studies in epidemi-
ology: A proposal for reporting. Meta-analysis
Of Observational Studies in Epidemiology
(MOOSE) group. JAMA 2000; 283:2008 –2012
24. Clinical guidelines on the identification,
evaluation, and treatment of overweight and
obesity in adults: The Evidence Report. Na-
tional Institutes of Health. Obes Res 1998;
6(Suppl 2):51S–209S
25. Laupacis A, Wells G, Richardson WS, et al:
Users’ guides to the medical literature: V.
How to use an article about prognosis. Evi-
dence-Based Medicine Working Group. JAMA
1994; 272:234 –237
26. Hurlburt R: Comprehending Behavioral Sta-
tistics. Third Edition. Belmont, CA, Brooks/
Cole, 2003
27. DerSimonian R, Laird N: Meta-analysis in
clinical trials. Control Clin Trials 1986;
7:177–188
28. Higgins JP, Thompson SG: Quantifying het-
erogeneity in a meta-analysis. Stat Med 2002;
21:1539 –1558
29. Deeks J, Higgins J, Altman D: Analyzing and
presenting results. In: Cochrane Reviewers’
Handbook 422. Alderson P, Green S, Higgins
J (Eds). Chichester, UK, John Wiley and
Sons, 2004, pp 68 –139
30. Klasen J, Junger A, Hartmann B, et al: In-
creased body mass index and peri-operative
risk in patients undergoing non-cardiac sur-
gery. Obes Surg 2004; 14:275–281
31. Choban PS, Weireter LJ, Maynes C: Obesity
and increased mortality in blunt trauma.
J Trauma 1991; 31:1253–1257
32. Byrnes MC, McDaniel MD, Moore MB, et al:
The effect of obesity on outcomes among
injured patients. J Trauma 2005; 58:
232–237
33. Duane TM, Dechert T, Aboutanos MB, et al:
Obesity and outcomes after blunt trauma.
J Trauma 2006; 61:1218 –1221
34. Abbasi AA: Body mass index as predictor of
outcome in critically ill patients in intensive
care unit. Abstr. Crit Care Med 2000; 28:A115
35. Yaegashi M, Jean R, Zuriqat M, et al: Out-
come of morbid obesity in the intensive care
unit. J Intensive Care Med 2005; 20:147–154
36. Duarte AG, Justino E, Bigler T, et al: Out-
comes of morbidly obese patients requiring
mechanical ventilation for acute respiratory
failure. Crit Care Med 2007; 35:732–737
37. Murillo LC, Restrepo AM, Hinestrosa F, et al:
Obesity is associated with improved survival
in critically ill patients with blood stream
infections. Chest 2006; 130:220S
38. Rivera-Fernandez R, Diaz-Contreras R, Chav-
ero-Magro MJ: Mortality and prognostic in-
dexes in obese patients admitted to the in-
tensive care unit. Med Intensiva 2006; 30:
162–166
39. Zein JG, Albrecht RM, Tawk MM, et al: Effect
of obesity on mortality in severely injured
blunt trauma patients remains unclear. Arch
Surg 2005; 140:1130 –1131
157Crit Care Med 2008 Vol. 36, No. 1
Page 7
40. Finkielman JD, Gajic O, Afessa B: Under-
weight is independently associated with
mortality in post-operative and non-
operative patients admitted to the inten-
sive care unit: A retrospective study. BMC
Emerg Med 2004; 4:3
41. Allison D, Faith M, Heo M, et al: Hypothesis
concerning the U-shaped relation between
body mass index and mortality. Am J Epide-
miol 1997; 146:339 –349
42. Lord G, Matarese G, Howard J, et al: Leptin
modulates the T-cell immune response and
reverses starvation-induced immunosup-
pression. Nature 1998; 394:897–901
43. Mancuso P, Gottschalk A, Phare SM, et al:
Leptin-deficient mice exhibit impaired host
defense in Gram-negative pneumonia. J Im-
munol 2002; 168:4018 4024
44. Moore SI, Huffnagle GB, Chen GH, et al:
Leptin modulates neutrophil phagocytosis of
K. pneumoniae. Infect Immun 2003; 71:
4182– 4185
45. Bornstein SR, Licinio J, Tauchnitz R, et al:
Plasma leptin levels are increased in survi-
vors of acute sepsis: Associated loss of diur-
nal rhythm, in cortisol and leptin secretion.
J Clin Endocrinol Metab 1998; 83:280 –283
46. Fiorentino DF, Zlotnik A, Mosmann TF, et al:
IL-10 inhibits cytokine production by acti-
vated macrophages. J Immunol 1991; 147:
3815–3822
47. Divangahi M, Demoule A, Danialou G, et al:
Impact of IL-10 on diaphragmatic cytokine
expression and contractility during Pseudo-
monas infection. Am J Respir Cell Mol Biol
2007; 36:504 –512
48. Fonarow GC, Srikanthan P, Costanzo M, et
al: An obesity paradox in acute heart failure:
Analysis of body mass index and inhospital
mortality for 108927 patients in the Acute
Decompensated Heart Failure National Reg-
istry. Am Heart J 2007; 153:74 81
49. Jin R, Grunkemeier GL, Furnary AP, et al: Is
obesity a risk factor for mortality in coronary
artery bypass surgery? Circulation 2005; 111:
3359 –3365
50. Lindhout AH, Wouters CW, Noyez L: Influ-
ence of obesity on in-hospital and early mor-
tality and morbidity after myocardial revas-
cularization. Eur J Cardiothorac Surg 2004;
26:535–541
51. Pelosi P, Croci M, Ravagnan I, et al: Total
respiratory system, lung, and chest wall me-
chanics in sedated-paralyzed postoperative
morbidly obese patients. Chest 1996; 109:
144 –151
52. Kress JP, Pohlman AS, Alverdy J, et al: The
impact of morbid obesity on oxygen cost of
breathing (VO
(2RESP)
) at rest. Am J Respir
Crit Care Med 1999; 160:883– 886
158 Crit Care Med 2008 Vol. 36, No. 1
Page 8
  • Source
    • "Notably, the hospital LOS was significantly longer among obese patients with pelvic, tibial, and fibular fractures than among normal-weight patients. This finding is consistent with previous reports that obesity increases the risk of non-union of fractures and complicates trauma recovery [20] and that delay of recovery is directly correlated with the severity of obesity [41]. In addition to the high risk of a range of medical conditions associated with obesity, including HTN, DM, cardiac disease, and pulmonary thromboembolism, their presence may also delay recovery [42] . "
    Preview · Article · Dec 2016 · BMC Public Health
  • Source
    • "In addition, energy storage may play a role in decreased mortality among obese patients in need of critical care [39]. The obesity paradox has been reported in patients with stroke, myocardial infarction, heart failure, renal disease, diabetes or intensive care patients [40][41][42][43][44]. Some authors argued that the apparent obesity paradox was due to selection bias [45,46]. "
    [Show abstract] [Hide abstract] ABSTRACT: Objectives: The objective of this study was to examine the association between obesity and all-cause mortality, length of stay and hospital cost among patients with sepsis 20 years of age or older. Materials and methods: It was a retrospective cohort study. The dataset was the Nationwide Inpatient Sample 2011, the largest publicly available all-payer inpatient care database in the United States. Hospitalizations of sepsis patients 20 years of age or older were included. All 25 primary and secondary diagnosis fields were screened to identify patients with sepsis using International Classification of Diseases, Ninth Revision, Clinical Modification codes. Obesity was the exposure of interest. It was one of the 29 standardized Elixhauser comorbidity measures and readily available in the dataset as a dichotomized variable. The outcome measures were all-cause in-hospital death, length of stay and hospital cost. Results: After weighting, our sample projected to a population size of 1,763,000, providing an approximation for the number of hospital discharges of all sepsis patients 20 years of age or older in the US in 2011. The overall all-cause mortality rate was 14.8%, the median hospital length of stay was 7 days and the median hospital cost was $15,917. After adjustment, the all-cause mortality was lower (adjusted OR = 0.84; 95% CI = 0.81 to 0.88); the average hospital length of stay was longer (adjusted difference = 0.65 day; 95% CI = 0.44 to 0.86) and the hospital cost per stay was higher (adjusted difference = $2,927; 95% CI = $1,606 to $4,247) for obese sepsis patients as compared to non-obese ones. Conclusion: With this large and nationally representative sample of over 1,000 hospitals in the US, we found that obesity was significantly associated with a 16% decrease in the odds of dying among hospitalized sepsis patients; however it was also associated with greater duration and cost of hospitalization.
    Full-text · Article · Apr 2016 · PLoS ONE
  • Source
    • "In France, this rate tends to be low with 11% of the population classified as obese in 2003 [33]. After multiple controversies [34], obesity seems to be associated with decreased complications, morbidity and mortality in critically ill patients [35][36][37] . In contrast , obesity has been associated with a worse outcome in trauma patients [38][39][40][41][42]. "
    [Show abstract] [Hide abstract] ABSTRACT: Background: Prediction of massive transfusion (MT) is challenging in management of trauma patients. However, MT and its prediction were poorly studied in obese patients. The main objective was to assess the relationship between obesity and MT needs in trauma patients. The secondary objectives were to validate the Trauma Associated Severe Hemorrhage (TASH) score in predicting MT in obese patients and to use a grey zone approach to optimize its ability to predict MT. Methods and findings: An observational retrospective study was conducted in a Level I Regional Trauma Center Trauma in obese and non-obese patients. MT was defined as ≥10U of packed red blood cells in the first 24h and obesity as a BMI≥30kg/m². Between January 2008 and December 2012, 119 obese and 791 non-obese trauma patients were included. The rate of MT was 10% (94/910) in the whole population. The MT rate tended to be higher in obese patients than in non-obese patients: 15% (18/119, 95%CI 9‒23%) versus 10% (76/791, 95%CI 8‒12%), OR, 1.68 [95%CI 0.97‒2.92], p = 0.07. After adjusting for Injury Severity Score (ISS), obesity was significantly associated with MT rate (OR, 1.79[95%CI 1.00‒3.21], p = 0.049). The TASH score was higher in the obese group than in the non-obese group: 7(4-11) versus 5(2-10)(p<0.001). The area under the ROC curves of the TASH score in predicting MT was very high and comparable between the obese and non-obese groups: 0.93 (95%CI, 0.89‒0.98) and 0.94 (95%CI, 0.92‒0.96), respectively (p = 0.80). The grey zone ranged respectively from 10 to 13 and from 9 to 12 in obese and non obese patients, and allowed separating patients at low, intermediate or high risk of MT using the TASH score. Conclusions: Obesity was associated with a higher rate of MT in trauma patients. The predictive performance of the TASH score and the grey zones were robust and comparable between obese and non-obese patients.
    Full-text · Article · Mar 2016 · PLoS ONE
Show more