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Original Research: CRITICAL CARE MEDICINE |

The Association Between Body Mass Index and Clinical Outcomes in Acute Lung Injury* FREE TO VIEW

Amy E. Morris, MD; Renee D. Stapleton, MD, MSc; Gordon D. Rubenfeld, MD, MSc; Leonard D. Hudson, MD, FCCP; Ellen Caldwell, MS; Kenneth P. Steinberg, MD, FCCP
Author and Funding Information

*From the Department of Medicine, Division of Pulmonary and Critical Care Medicine, University of Washington School of Medicine and Harborview Medical Center, Seattle, WA.

Correspondence to: Gordon Rubenfeld, MD, MSc,Division of Pulmonary and Critical Care Medicine, Harborview Medical Center, Mailbox 359762, 325 Ninth Ave, Seattle, WA 98104; e-mail: nodrog@u.washington.edu



Chest. 2007;131(2):342-348. doi:10.1378/chest.06-1709
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Background: The association between body mass index (BMI) and outcomes in critically ill patients is unclear. Our objective was to determine the association between BMI and outcomes in a population-based cohort of patients with acute lung injury (ALI).

Methods: In a prospective cohort study of all ICU patients in King County, Washington, with ALI in 1 year (1999 to 2000), 825 patients had a BMI recorded. Using multivariate analysis, patients in the abnormal BMI groups were compared to normal patients in the following areas: mortality, hospital length of stay (LOS), ICU LOS, duration of mechanical ventilation, and discharge disposition.

Results: There was no mortality difference in any of the abnormal BMI groups compared to normal-weight patients. Severely obese patients had longer hospital LOS than normal-weight patients (mean increase, 10.5 days; 95% confidence interval [CI], 4.8 to 16.2 days; p < 0.001); this was accentuated when analysis was restricted to survivors (mean increase, 14.3 days; 95% CI, 7.1 to 21.6 days; p < 0.001). ICU LOS and duration of mechanical ventilation were also longer in the severely obese group when analysis was restricted to survivors (mean increase, 5.6 days; 95% CI, 1.3 to 9.8 days; p = 0.01; and mean increase, 4.1 days; 95% CI, 0.4 to 7.7 days, respectively; p = 0.03). Severely obese patients were more likely to be discharged to a rehabilitation or skilled nursing facility than to home.

Conclusions: BMI is not associated with mortality in patients with ALI, but severe obesity is associated with increased morbidity and resource utilization in the hospital and after discharge.

Figures in this Article

Reports indicate that the prevalence of obesity in the United States is increasing dramatically. In 2000, almost two thirds of Americans were overweight; of these, nearly half were obese, with a body mass index (BMI) > 30 kg/m2.12 Severe obesity is increasing as well. In 1988, 2.7% of Americans had a BMI > 40 kg/m2; in 2000, this number had grown to 4.7%, or an estimated 13 million individuals.,12

Obesity is associated with chronic diseases including coronary artery and peripheral vascular disease, diabetes, osteoarthritis, and depression, as well as an overall decrease in life expectancy.35 The relative risk of death in obese patients has been estimated to be 1.9 times and 2.7 times that of normal-weight patients for women and men, respectively.4 The number of annual deaths attributable to obesity in the United States has been estimated at > 110,000.67

Outcome studies of hospitalized obese patients have shown that obesity is associated with an increased risk of complications or death following trauma, orthopedic surgery,812 and possibly cardiovascular events and procedures.1314 Results of observational studies in critically ill obese patients are less consistent, with some studies finding worse outcomes in obese ICU patients,1518 and others demonstrating no difference1922 or even lower mortality.23

Acute lung injury (ALI) and its more severe subtype ARDS are complications of critical illness or injury resulting in hypoxemic respiratory failure,24with an annual incidence in the United States estimated at 190,600 cases per year and contributing to > 70,000 deaths.25 Two of the studies described above investigated patients with this diagnosis, but neither were population based. To clarify the relationship between BMI and ICU outcomes, particularly in patients with ALI, we investigated a geographically defined population-based cohort of patients with ALI/ARDS across a broad range of BMI categories.

This study examined patients from the King County Lung Injury Project (KCLIP), a prospective cohort study of all patients with ALI admitted to all 18 hospitals with ICUs in King County, Washington, and 3 hospitals in adjacent counties between April 1999 and July 2000. A detailed description of the methods and hospitals is published elsewhere.25All patients receiving mechanical ventilation at these 21 hospitals were screened for enrollment using the American-European Consensus Conference definition of ALI,26 yielding a total of 1,113 patients. Of these, 825 patients had height and weight recorded at hospital admission; these patients form the cohort for our investigation. The study was approved by the University of Washington institutional review board as well as individual site institutional review boards when necessary.

In accordance with conventional practice as adapted from the National Heart, Lung, and Blood Institute guidelines,27patients were classified into the following BMI groups: < 18.5 kg/m2 (underweight), 18.5 to 24.9 kg/m2 (normal), 25 to 34.9 kg/m2 (overweight), 35.0 to 39.9 kg/m2 (obese), and ≥ 40.0 kg/m2 (severely obese). Demographic information included age, gender, comorbid conditions, ALI risk factor, and APACHE (acute physiologic and chronic health evaluation)-III score28 at hospital admission. Outcomes of interest were all-cause ICU and hospital mortality, hospital length of stay (LOS), ICU LOS, duration of mechanical ventilation, and discharge disposition. Survivor discharge locations were as follows: other hospital, long-term acute care facility (LTAC) [facilities designed for long-term patients who require prolonged ventilator weaning or other high-level care], skilled nursing facility (SNF) [equivalent to nursing home in our analyses], inpatient rehabilitation, or home. In cases wherein discharge disposition did not neatly fit into these categories, “other” was used.

Univariate analyses were performed with Wilcoxon rank-sum tests for continuous variables and χ2 tests for categorical variables. Multivariate linear (for continuous variables) and logistic (for categorical variables) regressions with robust SEs were used to evaluate the association between BMI and clinical outcomes with adjustment for potential confounders. LOS data were not log transformed in the analyses presented below, since our large sample size was robust to normality.29 These data were, however, log transformed in an additional sensitivity analysis.

We hypothesized that age, severity of illness, and risk factor for ALI were likely confounders of the relationship between BMI and clinical outcomes; these variables were included in all multivariate models. To avoid collinearity between age and total APACHE-III score, we included age and both the acute and chronic illness scores of the APACHE-III score in our models. Risk factor for ALI was categorized as sepsis (pulmonary or extrapulmonary), trauma, or other. We elected not to include ventilator tidal volume in our models because we believe it may be in the causal pathway between obesity and clinical outcomes.

BMI categories were fit as indicator variables; age, acute physiology score, and chronic illness score were fit as linear continuous variables. For morbidity outcomes, regression analyses were repeated with restriction to survivors in order to eliminate any effect of death on these outcomes. We also assessed effect modification by age on the relationship between BMI and morbidity outcomes by adding an interaction term to the models. Odds of discharge to a SNF, LTAC, other institution, and rehabilitation center were modeled with pairwise comparisons to discharge home as the reference category. In addition to the a priori confounders above, we also adjusted for admission living arrangements with indicator variables in this model. Statistical significance was defined as a two-sided p value ≤ 0.05.

There were no significant demographic differences between the 825 included patients and the 288 patients excluded for lack of BMI data. Among the study population, we found no significant differences in gender or severity of illness between the BMI groups. There were significant differences in age, ALI risk factor, and tidal volume on day 3 (Table 1 ). Age steadily decreased as BMI increased; severely obese patients had a median age of 54.7 years, compared to 61.5 years in the normal-weight group and 64.7 years in the underweight group (p < 0.001). Obese patients also had different risk factors for ALI (p < 0.05) than normal-weight patients, although in all groups sepsis from a suspected pulmonary source was the most common risk factor. Ventilator tidal volume (milliliter per kilogram of predicted body weight) on day 3 increased steadily as BMI increased (p < 0.001).

Crude mortality was highest in underweight patients (44.0%) and decreased as BMI increased (25.9% in BMI > 40 kg/m2). Unadjusted median hospital and ICU LOS and duration of mechanical ventilation were not significantly different between BMI groups.

After adjusting for age, chronic health points, acute physiology score, and risk factor for ALI, there was no statistically significant difference in mortality between any BMI category and normal-weight patients (Fig 1 ). We did, however, find a significantly longer adjusted hospital LOS in severely obese patients, who remained in the hospital an average of 10.5 days (95% confidence interval [CI], 4.8 to 16.2 days; p < 0.001) longer than normal-weight patients (Fig 2 ). This difference markedly increased in the severely obese group when the analysis was restricted to survivors, who had a mean adjusted stay 14.3 days longer than normal-weight patients (95% CI, 7.1 to 21.6 days; p < 0.001). Surviving severely obese patients also had a significantly longer ICU LOS and duration of mechanical ventilation compared to surviving normal-weight patients (mean adjusted increase, 5.6 days; 95% CI, 1.3 to 9.8 days; p = 0.01; and mean adjusted increase, 4.1 days; 95% CI, 0.4 to 7.7 days, respectively; p = 0.03). Age did not modify the association of BMI with hospital LOS, ICU LOS, or duration of mechanical ventilation (Table 2 ). Morbidity analysis repeated with log transformation of the LOS and duration of mechanical ventilation variables demonstrated a similar pattern in the severely obese patients (data not shown).

Severely obese patients were also more likely to require a higher level of care on discharge from the hospital (Table 3 ). With home as the reference discharge disposition, severely obese patients were significantly more likely to be discharged to a rehabilitation facility (odds ratio [OR] 6.0; 95% CI, 1.8 to 20.2) or an SNF (OR, 4.3; 95% CI, 1.5 to 12.5) than normal-weight patients. There was no difference in the discharge patterns to other hospitals or to LTACs.

This study examines the relationship between BMI and outcomes in a large population-based cohort of patients with ALI. After adjustment for confounders, there was no association between mortality and BMI, but we did identify significantly increased morbidity, as measured by longer hospital and ICU LOS, longer duration of mechanical ventilation, and more frequent discharge to an SNF or rehabilitation facility in patients with BMI > 40 kg/m2 compared to normal-weight patients. This was particularly true among survivors, who remained in the ICU and hospital 5.6 days and 14.3 days longer, respectively, and remained on the ventilator 4.1 days longer than normal-weight patients.

One previous study,21 a secondary analysis of 807 patients enrolled in a trial of reduced vs traditional tidal volumes conducted by the ARDS Network, also examined the role of obesity in outcomes of patients with ALI. Underweight patients were not examined, and only a small percentage (4.7%) of the study group was severely obese (BMI > 40 kg/m2), as a height to weight ratio ≥ 1.0 was an exclusion criterion in the original trial. No significant difference was found in 28-day or 180-day mortality rates, rate of unassisted ventilation by day 28, or ventilator-free days between normal-weight and obese patients. Other morbidity end points were not examined. More recently, the same group,15 reviewed outcomes from the Project Impact subscription database, defining the sample as patients who had an ICU admission diagnosis consistent with ALI and were intubated within 24 h of admission. Underweight patients in this group had a higher adjusted mortality than normal-weight patients. Although patients in the obese categories had an OR of death < 1, only the most obese (BMI, 30 to 39.9 kg/m2) met statistical significance. Unadjusted LOS and discharge location did not differ by BMI category.

Our results concerning survival differ from the established literature reporting increased mortality in underweight patients. However, this group represents a minority of the patients included in published studies.20,2223,30 Better studied is mortality in obese patients, and our results add to the preponderance of data that indicate a lack of significant mortality difference between normal-weight and obese patients. Our morbidity outcomes provide new information, particularly in regards to patients with ALI, for whom morbidity outcomes have not yet been well described using multivariate analysis. A major strength of our study lies in its reflection of a broadly generalizable, community-based population of ALI patients rather than a restricted group who met eligibility for a trial or participated in a voluntary database. There may be a substantive difference between patients with ALI and other critical illness, although two other large studies20,22 of seriously or critically ill patients also identified a lack of independent association of obesity with mortality, using sound epidemiologic methods with adjustment for relevant confounders.

The prolonged hospital and ICU LOS we identified in severely obese patients with ALI have been reported by other studies,1718,22 and in our cohort was accounted for in part by longer duration of mechanical ventilation among survivors. One prior study17 identified a similar pattern; in another study,21 in which patients received protocolized ventilator management and weaning strategies, there were no differences in mechanical ventilation end points. KCLIP is an observational community-based study performed before publication of the ARDS Network low tidal volume trial31and without inclusion of protocols. Previous research32 has suggested that older patients meet weaning criteria at the same time as their younger counterparts in similar clinical circumstances but are extubated later, suggesting that the decision to extubate may be influenced by a patient’s age in addition to objective data regarding likelihood of success. A similar situation may exist regarding severely obese patients, whose extubation might be viewed as risky due to airway concerns. The prolonged intubation time in these patients may therefore not be entirely due to physiologic factors predisposing to ventilator dependence, but at least in part to physician preconceptions about obese patients.

We also found that tidal volume consistently increased with increasing BMI. Since high tidal volumes have been found to reduce survival in patients with ALI,31 we a priori chose not to include tidal volume in our multivariate models because we believed it may be in the causal pathway to our outcomes of interest. One would expect severely obese patients to have increased mortality as a result of receiving tidal volumes now known to be injurious. The fact that severely obese patients in this cohort had tidal volumes that exceeded what is now recommended practice in ARDS lends further validity to our finding that this group of patients does not in fact have higher mortality than those of normal weight.

After discharge, severely obese patients were significantly more likely than normal patients to be discharged to a rehabilitation facility or SNF rather than home. As a reflection of the higher level of care these patients require even after their hospital stay, this finding provides further evidence that obese patients experience higher morbidity than their normal counterparts, and also incur higher health-care costs.

There are several limitations of our study. Despite strict screening criteria, misclassification of ALI in obese patients could have led to incorrect case ascertainment. The diagnosis of ALI in the most obese patients can be difficult due to body habitus, particularly regarding radiographic changes. Additionally, our sample sizes of underweight and severely obese patients are relatively small, thus limiting our power to detect small mortality differences between patients with normal and abnormal BMI. KCLIP is an observational database, and as such the accuracy of height and weight measurements is subject to the practices at each institution; instances wherein these values were estimated rather than measured could affect BMI category sample size.33 Further, as with any observational study, residual confounding from unmeasured variables is possible.

In this geographically defined population-based study, we demonstrate that the survival of severely obese patients with ALI does not differ from normal-weight patients. However, severely obese patients with ALI do have increased morbidity as measured by duration of mechanical ventilation and LOS, and they are more likely than normal-weight patients to require care in a rehabilitation facility or SNF after hospital discharge. As the US population becomes more overweight, longer LOS may have significant implications for health-care costs. Given this, severely obese patients may be a target population for intervention studies to address the causes of and to reduce their greater resource utilization. Additionally, the results of our study may be useful for prognostication by clinicians caring for critically ill obese patients and their families. In the primary care arena, subtle bias has been demonstrated to affect physician behavior and possibly quality of care for obese patients34; the same bias may affect ICU practice. It is important that critical care physicians become aware of the preponderance of data now suggesting that BMI is not independently associated with mortality in the ICU.

Abbreviations: ALI = acute lung injury; APACHE = acute physiologic and chronic health evaluation; BMI = body mass index; CI = confidence interval; KCLIP = King County Lung Injury Project; LOS = length of stay; LTAC = long-term acute care facility; OR = odds ratio; SNF = skilled nursing facility

This research was partially supported by Specialized Center of Research Grant HL-30542 in Acute Lung Injury from the National Heart, Lung, and Blood Institute, National Institutes of Health, and by 8K12RR023265–02 from the National Institutes of Health Roadmap/National Center for Research Resources.

None of the authors have conflicts of interest regarding this research.

Table Graphic Jump Location
Table 1. Baseline Characteristics by BMI Category*
* 

Data are presented as mean ± SD or No. (%) unless otherwise indicated.

 

Wilcoxon rank-sum test for trend.

 

Cochran-Armitage test for trend.

§ 

Millileters per kilogram of predicted body weight: women, 45 + 2.3 × (height in inches − 60); men, 50 + 2.3 × (height in inches − 60).

Figure Jump LinkFigure 1. OR of death in each BMI category compared to normal-weight patients, after adjusting for age, acute physiology score, chronic health points, and etiology of ALI. There was no statistically significant difference in mortality between any BMI category and normal-weight patients. Error bars show 95% CI.Grahic Jump Location
Figure Jump LinkFigure 2. Mean difference in duration of hospital LOS, ICU LOS, and mechanical ventilation (Mech. Vent.), in days, in each BMI category compared to normal-weight patients. After adjusting for age, acute physiology score, chronic health points, and etiology of ALI, severely obese patients had longer hospital LOS than normal-weight patients. This association was magnified when analyses were restricted to survivors, who also had significantly longer ICU LOS and duration of mechanical ventilation than normal-weight patients. Error bars show 95% CI.Grahic Jump Location
Table Graphic Jump Location
Table 2. Unadjusted Outcomes Among All Patients and Survivors*
* 

Data are presented as mean ± SD or No. (%). Data are presented as mean ± SD rather than median and interquartile range because variables were entered in multivariate analysis without log transformation, as described in the “Materials and Methods” section.

 

Cochran-Armitage test for trend.

 

Wilcoxon rank-sum test for trend.

Table Graphic Jump Location
Table 3. Adjusted Discharge Disposition Outcomes Among Survivors*
* 

Data are presented as OR (95% CI; p value) of discharge from hospital to each location for patients in each BMI category compared to normal-weight patients. Reference category is home. Values are adjusted for admission source, age, acute physiology score, chronic health points, and etiology of ALI. N/A = no patients in this category.

Flegal, KM, Carroll, MD, Ogden, CL, et al (2002) Prevalence and trends in obesity among US adults, 1999–2000.JAMA288,1723-1727. [PubMed] [CrossRef]
 
Flegal, KM, Carroll, MD, Kuczmarski, RJ, et al Overweight and obesity in the United States: prevalence and trends, 1960–1994.Int J Obes Relat Metab Disord1998;22,39-47. [PubMed]
 
Screening for obesity in adults: recommendations and rationale.Ann Intern Med2003;139,930-932. [PubMed]
 
Calle, EE, Thun, MJ, Petrelli, JM, et al Body-mass index and mortality in a prospective cohort of U.S. adults.N Engl J Med1999;341,1097-1105. [PubMed]
 
Peeters, A, Barendregt, JJ, Willekens, F, et al Obesity in adulthood and its consequences for life expectancy: a life-table analysis.Ann Intern Med2003;138,24-32. [PubMed]
 
Flegal, KM, Graubard, BI, Williamson, DF, et al Excess deaths associated with underweight, overweight, and obesity.JAMA2005;293,1861-1867. [PubMed]
 
Allison, DB, Fontaine, KR, Manson, JE, et al Annual deaths attributable to obesity in the United States.JAMA1999;282,1530-1538. [PubMed]
 
Morris, CD, Sepkowitz, K, Fonshell, C, et al Prospective identification of risk factors for wound infection after lower extremity oncologic surgery.Ann Surg Oncol2003;10,778-782. [PubMed]
 
Japour, C, Vohra, P, Giorgini, R, et al Ankle arthroscopy: follow-up study of 33 ankles; effect of physical therapy and obesity.J Foot Ankle Surg1996;35,199-209. [PubMed]
 
Neville, AL, Brown, CV, Weng, J, et al Obesity is an independent risk factor of mortality in severely injured blunt trauma patients.Arch Surg2004;139,983-987. [PubMed]
 
Choban, PS, Weireter, LJ, Jr, Maynes, C Obesity and increased mortality in blunt trauma.J Trauma1991;31,1253-1257. [PubMed]
 
Winiarsky, R, Barth, P, Lotke, P Total knee arthroplasty in morbidly obese patients.J Bone Joint Surg Am1998;80,1770-1774. [PubMed]
 
Rockx, MA, Fox, SA, Stitt, LW, et al Is obesity a predictor of mortality, morbidity and readmission after cardiac surgery?Can J Surg2004;47,34-38. [PubMed]
 
Schwann, TA, Habib, RH, Zacharias, A, et al Effects of body size on operative, intermediate, and long-term outcomes after coronary artery bypass operation.Ann Thorac Surg2001;71,521-530. [PubMed]
 
O’Brien, JM, Jr, 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 Med2006;34,738-744. [PubMed]
 
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 Med2004;32,998-1003. [PubMed]
 
El-Solh, A, Sikka, P, Bozkanat, E, et al Morbid obesity in the medical ICU.Chest2001;120,1989-1997. [PubMed]
 
Goulenok, C, Monchi, M, Chiche, JD, et al Influence of overweight on ICU mortality: a prospective study.Chest2004;125,1441-1445. [PubMed]
 
Ray, DE, Matchett, SC, Baker, K, et al The effect of body mass index on patient outcomes in a medical ICU.Chest2005;127,2125-2131. [PubMed]
 
Galanos, AN, Pieper, CF, Kussin, PS, et al Relationship of body mass index to subsequent mortality among seriously ill hospitalized patients: SUPPORT Investigators; The Study to Understand Prognoses and Preferences for Outcome and Risks of Treatments.Crit Care Med1997;25,1962-1968. [PubMed]
 
O’Brien, JM, Jr, Welsh, CH, Fish, RH, et al Excess body weight is not independently associated with outcome in mechanically ventilated patients with acute lung injury.Ann Intern Med2004;140,338-345. [PubMed]
 
Tremblay, A, Bandi, V Impact of body mass index on outcomes following critical care.Chest2003;123,1202-1207. [PubMed]
 
Garrouste-Orgeas, M, Troche, G, Azoulay, E, et al Body mass index: an additional prognostic factor in ICU patients.Intensive Care Med2004;30,437-443. [PubMed]
 
Ware, LB, Matthay, MA The acute respiratory distress syndrome.N Engl J Med2000;342,1334-1349. [PubMed]
 
Rubenfeld, GD, Caldwell, E, Peabody, E, et al Incidence and outcomes of acute lung injury.N Engl J Med2005;353,1685-1693. [PubMed]
 
Bernard, GR, Artigas, A, Brigham, KL, et al The American-European Consensus Conference on ARDS: definitions, mechanisms, relevant outcomes, and clinical trial coordination.Am J Respir Crit Care Med1994;149,818-824. [PubMed]
 
Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults: the evidence report. National Institutes of Health.Obes Res1998;6(suppl),51S-209S
 
Knaus, WA, Wagner, DP, Draper, EA, et al The APACHE III prognostic system: risk prediction of hospital mortality for critically ill hospitalized adults.Chest1991;100,1619-1636. [PubMed]
 
Lumley, T, Diehr, P, Emerson, S, et al The importance of the normality assumption in large public health data sets.Annu Rev Public Health2002;23,151-169. [PubMed]
 
Bo, M, Massaia, M, Raspo, S, et al Predictive factors of in-hospital mortality in older patients admitted to a medical intensive care unit.J Am Geriatr Soc2003;51,529-533. [PubMed]
 
Ventilation with lower tidal volumes as compared with traditional tidal volumes for acute lung injury and the acute respiratory distress syndrome. The Acute Respiratory Distress Syndrome Network.N Engl J Med2000;342,1301-1308. [PubMed]
 
Ely, EW, Wheeler, AP, Thompson, BT, et al Recovery rate and prognosis in older persons who develop acute lung injury and the acute respiratory distress syndrome.Ann Intern Med2002;136,25-36. [PubMed]
 
Bloomfield, R, Steel, E, MacLennan, G, et al Accuracy of weight and height estimation in an intensive care unit: implications for clinical practice and research.Crit Care Med2006;34,2153-2157. [PubMed]
 
Hebl, MR, Xu, J Weighing the care: physicians’ reactions to the size of a patient.Int J Obes Relat Metab Disord2001;25,1246-1252. [PubMed]
 

Figures

Figure Jump LinkFigure 1. OR of death in each BMI category compared to normal-weight patients, after adjusting for age, acute physiology score, chronic health points, and etiology of ALI. There was no statistically significant difference in mortality between any BMI category and normal-weight patients. Error bars show 95% CI.Grahic Jump Location
Figure Jump LinkFigure 2. Mean difference in duration of hospital LOS, ICU LOS, and mechanical ventilation (Mech. Vent.), in days, in each BMI category compared to normal-weight patients. After adjusting for age, acute physiology score, chronic health points, and etiology of ALI, severely obese patients had longer hospital LOS than normal-weight patients. This association was magnified when analyses were restricted to survivors, who also had significantly longer ICU LOS and duration of mechanical ventilation than normal-weight patients. Error bars show 95% CI.Grahic Jump Location

Tables

Table Graphic Jump Location
Table 1. Baseline Characteristics by BMI Category*
* 

Data are presented as mean ± SD or No. (%) unless otherwise indicated.

 

Wilcoxon rank-sum test for trend.

 

Cochran-Armitage test for trend.

§ 

Millileters per kilogram of predicted body weight: women, 45 + 2.3 × (height in inches − 60); men, 50 + 2.3 × (height in inches − 60).

Table Graphic Jump Location
Table 2. Unadjusted Outcomes Among All Patients and Survivors*
* 

Data are presented as mean ± SD or No. (%). Data are presented as mean ± SD rather than median and interquartile range because variables were entered in multivariate analysis without log transformation, as described in the “Materials and Methods” section.

 

Cochran-Armitage test for trend.

 

Wilcoxon rank-sum test for trend.

Table Graphic Jump Location
Table 3. Adjusted Discharge Disposition Outcomes Among Survivors*
* 

Data are presented as OR (95% CI; p value) of discharge from hospital to each location for patients in each BMI category compared to normal-weight patients. Reference category is home. Values are adjusted for admission source, age, acute physiology score, chronic health points, and etiology of ALI. N/A = no patients in this category.

References

Flegal, KM, Carroll, MD, Ogden, CL, et al (2002) Prevalence and trends in obesity among US adults, 1999–2000.JAMA288,1723-1727. [PubMed] [CrossRef]
 
Flegal, KM, Carroll, MD, Kuczmarski, RJ, et al Overweight and obesity in the United States: prevalence and trends, 1960–1994.Int J Obes Relat Metab Disord1998;22,39-47. [PubMed]
 
Screening for obesity in adults: recommendations and rationale.Ann Intern Med2003;139,930-932. [PubMed]
 
Calle, EE, Thun, MJ, Petrelli, JM, et al Body-mass index and mortality in a prospective cohort of U.S. adults.N Engl J Med1999;341,1097-1105. [PubMed]
 
Peeters, A, Barendregt, JJ, Willekens, F, et al Obesity in adulthood and its consequences for life expectancy: a life-table analysis.Ann Intern Med2003;138,24-32. [PubMed]
 
Flegal, KM, Graubard, BI, Williamson, DF, et al Excess deaths associated with underweight, overweight, and obesity.JAMA2005;293,1861-1867. [PubMed]
 
Allison, DB, Fontaine, KR, Manson, JE, et al Annual deaths attributable to obesity in the United States.JAMA1999;282,1530-1538. [PubMed]
 
Morris, CD, Sepkowitz, K, Fonshell, C, et al Prospective identification of risk factors for wound infection after lower extremity oncologic surgery.Ann Surg Oncol2003;10,778-782. [PubMed]
 
Japour, C, Vohra, P, Giorgini, R, et al Ankle arthroscopy: follow-up study of 33 ankles; effect of physical therapy and obesity.J Foot Ankle Surg1996;35,199-209. [PubMed]
 
Neville, AL, Brown, CV, Weng, J, et al Obesity is an independent risk factor of mortality in severely injured blunt trauma patients.Arch Surg2004;139,983-987. [PubMed]
 
Choban, PS, Weireter, LJ, Jr, Maynes, C Obesity and increased mortality in blunt trauma.J Trauma1991;31,1253-1257. [PubMed]
 
Winiarsky, R, Barth, P, Lotke, P Total knee arthroplasty in morbidly obese patients.J Bone Joint Surg Am1998;80,1770-1774. [PubMed]
 
Rockx, MA, Fox, SA, Stitt, LW, et al Is obesity a predictor of mortality, morbidity and readmission after cardiac surgery?Can J Surg2004;47,34-38. [PubMed]
 
Schwann, TA, Habib, RH, Zacharias, A, et al Effects of body size on operative, intermediate, and long-term outcomes after coronary artery bypass operation.Ann Thorac Surg2001;71,521-530. [PubMed]
 
O’Brien, JM, Jr, 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 Med2006;34,738-744. [PubMed]
 
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 Med2004;32,998-1003. [PubMed]
 
El-Solh, A, Sikka, P, Bozkanat, E, et al Morbid obesity in the medical ICU.Chest2001;120,1989-1997. [PubMed]
 
Goulenok, C, Monchi, M, Chiche, JD, et al Influence of overweight on ICU mortality: a prospective study.Chest2004;125,1441-1445. [PubMed]
 
Ray, DE, Matchett, SC, Baker, K, et al The effect of body mass index on patient outcomes in a medical ICU.Chest2005;127,2125-2131. [PubMed]
 
Galanos, AN, Pieper, CF, Kussin, PS, et al Relationship of body mass index to subsequent mortality among seriously ill hospitalized patients: SUPPORT Investigators; The Study to Understand Prognoses and Preferences for Outcome and Risks of Treatments.Crit Care Med1997;25,1962-1968. [PubMed]
 
O’Brien, JM, Jr, Welsh, CH, Fish, RH, et al Excess body weight is not independently associated with outcome in mechanically ventilated patients with acute lung injury.Ann Intern Med2004;140,338-345. [PubMed]
 
Tremblay, A, Bandi, V Impact of body mass index on outcomes following critical care.Chest2003;123,1202-1207. [PubMed]
 
Garrouste-Orgeas, M, Troche, G, Azoulay, E, et al Body mass index: an additional prognostic factor in ICU patients.Intensive Care Med2004;30,437-443. [PubMed]
 
Ware, LB, Matthay, MA The acute respiratory distress syndrome.N Engl J Med2000;342,1334-1349. [PubMed]
 
Rubenfeld, GD, Caldwell, E, Peabody, E, et al Incidence and outcomes of acute lung injury.N Engl J Med2005;353,1685-1693. [PubMed]
 
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    Print ISSN: 0012-3692
    Online ISSN: 1931-3543