BMI‐Related Outcome in Minority Patients

Obesity affects all segments of the American population. However, it imposes a larger burden and poses a greater threat to minority populations.1 The increase in overall prevalence of obesity and obesity‐related diseases are especially pronounced in ethnic minorities,2 and the outlook for minorities who develop obesity‐associated diseases such as stroke and chronic renal disease is worse than in their Caucasian counterparts.3

Despite the higher prevalence of obesity in ethnic minorities, the majority of research on the relationship between body mass index (BMI) and mortality has been conducted among Caucasians in the United States. This is due largely to the small number of minority participants in most studies, which makes for low statistical power.4

A curious epidemiologic paradox has been the observation, in many studies, that black adults have lower morbidity and mortality associated with obesity compared to Caucasians.5 In fact, some authors suggest that high BMI among black and other minorities may not be as strong a risk factor for mortality as it is in others.6, 7

Very few studies have specifically examined the contribution of BMI to postoperative outcome in a large cohort of minority patients.8, 9 Similarly, the authors are unaware of any previous studies describing the clinical relevance of being overweight and obese in minority patients undergoing surgery. Therefore, the primary objective of this observational study was to describe the prevalence of overweight and obesity in a large cohort of minority surgical patients, and the impact of BMI class on their postoperative outcome. Our a priori hypothesis was that obese minority surgical patients would have a poorer postoperative outcome and have higher 30‐day all‐cause mortality than normal weight individuals.

METHODS

Study data were derived from the Participant Use Data File of the American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP) for the calendar years 2005 to 2008. This multi‐institutional (186 participating centers) reporting system was designed to provide risk‐adjusted surgical outcome data from throughout the United States.

The methodology for collecting these data, including their accuracy and reproducibility, has been detailed in previous publications.10, 11 It is briefly reviewed here. Dedicated nurse clinical reviewers at each hospital prospectively enrolled patients and collected data in a standardized fashion according to strict ACS‐NSQIP definitions. A systematic sample was obtained by taking the first 40 cases per nurse reviewer on an 8‐day cycle from the operating room log, ensuring that no particular operating room day block time would bias the weighting of cases. Nurse reviewers had completed comprehensive training regarding definitions and data extraction, as well as continuing education and monitoring through the ACS‐NSQIP program. They are assessed for inter‐rater reliability during biennial site visits. Information was obtained from patient medical records, physician office records, and telephone interviews. Patients were followed through their hospital course and after discharge from hospital up to 30 days postoperatively. A high level of accuracy and reproducibility of the data have been previously demonstrated.12

Race was defined as African American, Hispanic, Asian or Pacific Islander, or American Indian/Alaskan native, as identified by the clinical care provider, or within the medical record. Patients were excluded if race was coded as white, or not recorded. We also excluded patients with missing record of height and/or weight. The final study cohort consisted of 119,619 minority patients. We then computed BMI as weight in kilograms divided by the square of the height in meters (BMI = kg/m²). Patients were classified as underweight (BMI 18.5 kg/m²), normal weight (BMI = 18.6‐24.9 kg/m²), overweight (BMI = 25‐29.9 kg/m²), obese (BMI = 30‐39.9 kg/m²), and morbidly obese (BMI 40 kg/m²) in accordance with National Institute of Health (NIH) standards.13

RESULTS

The study cohort included 119,619 surgical patients (Table 1). Their mean (standard deviation [SD]) age was 50.4 (16.9), and the mean (SD) BMI of 30.3 (8.9) kg/m² was in the obese range. The overall prevalence of high BMI (overweight or obese) was 70.8%. A very small proportion, 2.7%, of patients was classified as underweight. Sex‐stratified demographic and behavioral characteristics differed significantly across all the variables in our study cohort. Men were more likely to be overweight, whereas women were more likely to be obese or severely obese. A majority (77.4%) of the patients were non‐elderly adults (<65years) undergoing elective (85.9%) surgical procedures. The minority patients in this study were African American (50%), Hispanic (36%), Asian and Pacific Islander (10%), and American Indian and Alaskan native (4%).

The distribution of baseline preoperative clinical characteristics by BMI class revealed many significant differences (Table 2). Age was significantly different among the BMI classes, with the severely obese group being about 8 years younger than the underweight or normal weight group. Similarly, severely obese patients were more likely to be women, less likely to smoke, more likely to be hypertensive, diabetic, have a history of dyspnea at rest, and more likely to belong to high ASA class. On the other hand, underweight patients were more likely to have disseminated cancer, be current smokers, consume more than 2 alcoholic drinks per day, have active chronic obstructive pulmonary disease (COPD), and have ascites. They were also more likely to be on dialysis and have cardiac disease, as well as a history of stroke. Urgency of surgery also varied significantly across the BMI categories, with the underweight group having the highest incidence of emergency surgery (20.6%) and the severely obese group being the least likely to present for emergency surgery (8.2%).

Perioperative outcomes according to BMI classes documented significant differences (Table 3). Work relative value unit (Work RVU, a measure of surgical complexity), as well as total anesthesia and operation time decreased in a stepwise fashion across the BMI classes to the obese group, followed by increase in these parameters in the severely obese group. Following a decrease to the normal BMI category, there was a positive association between BMI and the incidence of postoperative superficial and deep wound infection, as well as wound disruption.

There was a negative association between BMI class and the likelihood of postoperative sepsis, septic shock, reintubation, delayed ventilator wean, and postoperative pneumonia. Similarly, the proportions of patients who developed postoperative acute renal failure, cardiac arrest, and those who required postoperative blood transfusion or needed reoperation, decreased significantly across the BMI classes, with the highest proportion of cases being in the underweight group and the lowest in the severely obese group. Overall composite morbidity was twice as high in the underweight compared to the severely obese group.

There were 1758 deaths among the study's 119,619 patients, resulting in an overall mortality rate of 1.5%. The overall major complication rate was 13.8%. The distribution of total mortality rate as well as mortality in patients with at least 1 major postoperative complication across BMI classes revealed consistent differences (Figure 1). Over the entire range of BMI classes, there was a progressive, stepwise decrease in the proportion of deaths with increasing BMI. This pattern also occurred among patients who developed at least 1 major postoperative complication, indicating a reduced likelihood of death after a major complication. This is reflective of a reduced likelihood of death after a major complication (failure to rescue) with increasing BMI.

Figure 1

Multivariate logistic regression defined a number of factors associated with 30‐day mortality (Table 4). The Hosmer and Lemeshow goodness‐of‐fit test for this model was not statistically significant (² = 17.8, df = 8, P = 0.23). High ASA physical status was associated with high odds of mortality. Specifically, when controlling for the other covariates in the model, ASA status was associated with a 5‐fold increased relative odds of death (adjusted odds ratio [OR] = 5.30; 95% confidence interval = 4.96‐5.79, P < 0.001). Similarly, occurrence of 1 or more major postoperative complication was associated with 6‐fold increased relative odds of mortality. The paradoxical effect of BMI category observed on univariate analysis was maintained in the multivariate model. Specifically, underweight patients had the highest relative odds of mortality, while severely obese patients had the lowest, compared with patients at a healthy weight (Table 4). Interestingly, smoking had no significant effect on the odds of mortality after controlling for other factors. Similarly, the specific racial group and the timing of the surgical intervention had no significant effect on mortality.

DISCUSSION

In this large, study of minority surgical patients, the impact of BMI on the 30‐day morbidity and mortality was unexpected. The working hypothesis was that overweight and obese patients would have a worse outcome after surgery. However, contrary to this hypothesis, the lowest all‐cause mortality rate was found in the severely obese (BMI 40 kg/m²) group in both men and women. Death rates decreased progressively in a stepwise fashion from the underweight to the severely obese group. Similarly, even in patients who developed at least 1 major postoperative complication, the likelihood of death was still negatively associated with BMI. This negative association of mortality with BMI was observed despite the higher prevalence of chronic diseases, such as hypertension, diabetes, and dyspnea at rest, in the increasing BMI classes.

Controversy remains regarding the association between BMI and mortality, in particular about the shape of the curve for the association between BMI and mortality. Epidemiologic studies have variously described J‐shaped, U‐shaped, monotonic, or linear relationships.16, 17 In the surgical population, a reverse J‐shaped relationship between BMI category and mortality has been described.18, 19 Sometimes this is referred to as obesity paradox or reverse epidemiology: a trend whereby overweight and moderately obese patients have better outcomes and lower risk of death than leaner patients.18 This phenomenon is particularly well described in adult20 and elderly heart failure and hypertensive patients.21 Many of these studies either had very few minority patients,21 or mortality pattern was not analyzed along ethnic lines.

Few studies10 have focused exclusively on minority surgical patients. Some investigators have determined that high BMI in black adults may not be as important a risk factor for mortality6, 7 as in whites. Our data suggest that among minority surgical patients, the relationship appeared to be a downward trend in mortality from low to high BMI, thus revealing the obesity paradox. This pattern was evident even in patients who developed 1 major complication in the postoperative period, suggesting that high BMI also protects against failure to rescueor death after a major complication.

Despite decades of research, the mechanisms underlying the obesity paradox remain speculative.20, 22. Many have posited that adiposity may confer protection against cytokines and various inflammatory mediators in heart failure patients by the production of buffering lipoproteins.23, 24 It is conceivable that similar protection against inflammatory response to surgical tissue trauma is operational in minority patients with high BMI. Another possible reason for the obesity paradox is the clinical presentation and disease progression at the time of surgery. Perhaps, similar to the observation in obese patients with heart failure,25 obese minority patients are symptomatic at an earlier stage of their disease than lean patients, making for earlier diagnosis and treatment. Thus, obesity may simply be a marker of less severe disease at the time of presentation.

Obese patients may also be more aggressively monitored and treated in the perioperative period than lean patients, because of the general perception that they are a high‐risk group.10 This may partly explain the decreased likelihood of failure to rescue with increasing BMI in our patients. Increased vigilance and prompt treatment of complications should reduce the overall morbidity and mortality rate in this group. It is also conceivable that a therapeutic selection bias is operational in the patients we studied. This describes scenarios where relatively healthy obese minority patients were operated upon, while sicker, morbidly obese patients were denied surgery due to perceived prohibitive risks. However, we would have expected a higher proportion of severely obese patients to present for emergency surgery, which is contrary to our finding of the lowest incidence of emergency surgery in the severely obese group. It is also possible that severe obesity may be associated with a higher attrition rate, such that the extremely obese patients did not live long enough to present for surgery. This is somewhat likely, given the significantly younger age of the severely obese patients in our study cohort. It is, however, impossible to determine survival effect from a cross‐sectional hospital‐based study design. Clearly, mechanisms used to explain the obesity paradox in minority surgical patients are likely to remain speculative, owing to the interaction of several factors such as concomitant comorbidities, disease progression at the time of presentation, patients' weight history, and regional fat distribution.

The current study confirms the findings of previous investigators26 about the importance of reducing major postoperative complications in surgical patients. While this may seem axiomatic, it deserves reiteration because the risk of postoperative mortality increases considerably in all the BMI categories following 1 or more major postoperative complication. However, it is not clear why obese and morbidly obese patients had a lower incidence of failure to rescue. This may be related to greater physiologic reserve in the obese and morbidly obese group, especially because patients in the higher BMI groups were significantly younger than the normal weight or lean patients. For the same reason, these younger, severely obese patients may have been more aggressively monitored and treated, thereby increasing the likelihood of being rescued following a major complication. It is also possible that the lower proportion of emergency procedures performed in obese and severely obese groups was somewhat protective, especially because emergency surgery was an independent predictor of overall mortality in this cohort of patients. In fact, when we stratified the patients according to urgency of surgery and explored the bivariate relationship between BMI category and mortality (data not shown) among those undergoing urgent surgery, the geometrical distribution of mortality did show a reverse‐J pattern with the highest proportion of cases in the underweight group, declining in the normal BMI and overweight group, and increasing steadily in obese and severely obese group. To this end, caution should be exercised when interpreting the association of BMI group with postoperative mortality for procedures performed as an emergency.

Smoking and antecedent illness are 2 confounding factors commonly criticized in studies attempting to associated BMI with mortality. This is because smokers tend to weigh less and have higher mortality rates than nonsmokers. The present investigation did not find a significant contribution of smoking to mortality when other factors included in a logistic regression model were considered. The current study's findings are consistent with those of previous data in African American patients,27 and contrasts with the excess mortality described in currently smoking Caucasian men and women.28 It is possible that smoking is not an important effect modifier when considering the relevance of BMI to postoperative mortality in minority patients.

Obesity affects all segments of the American population. However, it imposes a larger burden and poses a greater threat to minority populations.1 The increase in overall prevalence of obesity and obesity‐related diseases are especially pronounced in ethnic minorities,2 and the outlook for minorities who develop obesity‐associated diseases such as stroke and chronic renal disease is worse than in their Caucasian counterparts.3

Despite the higher prevalence of obesity in ethnic minorities, the majority of research on the relationship between body mass index (BMI) and mortality has been conducted among Caucasians in the United States. This is due largely to the small number of minority participants in most studies, which makes for low statistical power.4

A curious epidemiologic paradox has been the observation, in many studies, that black adults have lower morbidity and mortality associated with obesity compared to Caucasians.5 In fact, some authors suggest that high BMI among black and other minorities may not be as strong a risk factor for mortality as it is in others.6, 7

Very few studies have specifically examined the contribution of BMI to postoperative outcome in a large cohort of minority patients.8, 9 Similarly, the authors are unaware of any previous studies describing the clinical relevance of being overweight and obese in minority patients undergoing surgery. Therefore, the primary objective of this observational study was to describe the prevalence of overweight and obesity in a large cohort of minority surgical patients, and the impact of BMI class on their postoperative outcome. Our a priori hypothesis was that obese minority surgical patients would have a poorer postoperative outcome and have higher 30‐day all‐cause mortality than normal weight individuals.

METHODS

Study data were derived from the Participant Use Data File of the American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP) for the calendar years 2005 to 2008. This multi‐institutional (186 participating centers) reporting system was designed to provide risk‐adjusted surgical outcome data from throughout the United States.

The methodology for collecting these data, including their accuracy and reproducibility, has been detailed in previous publications.10, 11 It is briefly reviewed here. Dedicated nurse clinical reviewers at each hospital prospectively enrolled patients and collected data in a standardized fashion according to strict ACS‐NSQIP definitions. A systematic sample was obtained by taking the first 40 cases per nurse reviewer on an 8‐day cycle from the operating room log, ensuring that no particular operating room day block time would bias the weighting of cases. Nurse reviewers had completed comprehensive training regarding definitions and data extraction, as well as continuing education and monitoring through the ACS‐NSQIP program. They are assessed for inter‐rater reliability during biennial site visits. Information was obtained from patient medical records, physician office records, and telephone interviews. Patients were followed through their hospital course and after discharge from hospital up to 30 days postoperatively. A high level of accuracy and reproducibility of the data have been previously demonstrated.12

Race was defined as African American, Hispanic, Asian or Pacific Islander, or American Indian/Alaskan native, as identified by the clinical care provider, or within the medical record. Patients were excluded if race was coded as white, or not recorded. We also excluded patients with missing record of height and/or weight. The final study cohort consisted of 119,619 minority patients. We then computed BMI as weight in kilograms divided by the square of the height in meters (BMI = kg/m²). Patients were classified as underweight (BMI 18.5 kg/m²), normal weight (BMI = 18.6‐24.9 kg/m²), overweight (BMI = 25‐29.9 kg/m²), obese (BMI = 30‐39.9 kg/m²), and morbidly obese (BMI 40 kg/m²) in accordance with National Institute of Health (NIH) standards.13

RESULTS

The study cohort included 119,619 surgical patients (Table 1). Their mean (standard deviation [SD]) age was 50.4 (16.9), and the mean (SD) BMI of 30.3 (8.9) kg/m² was in the obese range. The overall prevalence of high BMI (overweight or obese) was 70.8%. A very small proportion, 2.7%, of patients was classified as underweight. Sex‐stratified demographic and behavioral characteristics differed significantly across all the variables in our study cohort. Men were more likely to be overweight, whereas women were more likely to be obese or severely obese. A majority (77.4%) of the patients were non‐elderly adults (<65years) undergoing elective (85.9%) surgical procedures. The minority patients in this study were African American (50%), Hispanic (36%), Asian and Pacific Islander (10%), and American Indian and Alaskan native (4%).

The distribution of baseline preoperative clinical characteristics by BMI class revealed many significant differences (Table 2). Age was significantly different among the BMI classes, with the severely obese group being about 8 years younger than the underweight or normal weight group. Similarly, severely obese patients were more likely to be women, less likely to smoke, more likely to be hypertensive, diabetic, have a history of dyspnea at rest, and more likely to belong to high ASA class. On the other hand, underweight patients were more likely to have disseminated cancer, be current smokers, consume more than 2 alcoholic drinks per day, have active chronic obstructive pulmonary disease (COPD), and have ascites. They were also more likely to be on dialysis and have cardiac disease, as well as a history of stroke. Urgency of surgery also varied significantly across the BMI categories, with the underweight group having the highest incidence of emergency surgery (20.6%) and the severely obese group being the least likely to present for emergency surgery (8.2%).

Perioperative outcomes according to BMI classes documented significant differences (Table 3). Work relative value unit (Work RVU, a measure of surgical complexity), as well as total anesthesia and operation time decreased in a stepwise fashion across the BMI classes to the obese group, followed by increase in these parameters in the severely obese group. Following a decrease to the normal BMI category, there was a positive association between BMI and the incidence of postoperative superficial and deep wound infection, as well as wound disruption.

There was a negative association between BMI class and the likelihood of postoperative sepsis, septic shock, reintubation, delayed ventilator wean, and postoperative pneumonia. Similarly, the proportions of patients who developed postoperative acute renal failure, cardiac arrest, and those who required postoperative blood transfusion or needed reoperation, decreased significantly across the BMI classes, with the highest proportion of cases being in the underweight group and the lowest in the severely obese group. Overall composite morbidity was twice as high in the underweight compared to the severely obese group.

There were 1758 deaths among the study's 119,619 patients, resulting in an overall mortality rate of 1.5%. The overall major complication rate was 13.8%. The distribution of total mortality rate as well as mortality in patients with at least 1 major postoperative complication across BMI classes revealed consistent differences (Figure 1). Over the entire range of BMI classes, there was a progressive, stepwise decrease in the proportion of deaths with increasing BMI. This pattern also occurred among patients who developed at least 1 major postoperative complication, indicating a reduced likelihood of death after a major complication. This is reflective of a reduced likelihood of death after a major complication (failure to rescue) with increasing BMI.

Figure 1

Multivariate logistic regression defined a number of factors associated with 30‐day mortality (Table 4). The Hosmer and Lemeshow goodness‐of‐fit test for this model was not statistically significant (² = 17.8, df = 8, P = 0.23). High ASA physical status was associated with high odds of mortality. Specifically, when controlling for the other covariates in the model, ASA status was associated with a 5‐fold increased relative odds of death (adjusted odds ratio [OR] = 5.30; 95% confidence interval = 4.96‐5.79, P < 0.001). Similarly, occurrence of 1 or more major postoperative complication was associated with 6‐fold increased relative odds of mortality. The paradoxical effect of BMI category observed on univariate analysis was maintained in the multivariate model. Specifically, underweight patients had the highest relative odds of mortality, while severely obese patients had the lowest, compared with patients at a healthy weight (Table 4). Interestingly, smoking had no significant effect on the odds of mortality after controlling for other factors. Similarly, the specific racial group and the timing of the surgical intervention had no significant effect on mortality.

DISCUSSION

In this large, study of minority surgical patients, the impact of BMI on the 30‐day morbidity and mortality was unexpected. The working hypothesis was that overweight and obese patients would have a worse outcome after surgery. However, contrary to this hypothesis, the lowest all‐cause mortality rate was found in the severely obese (BMI 40 kg/m²) group in both men and women. Death rates decreased progressively in a stepwise fashion from the underweight to the severely obese group. Similarly, even in patients who developed at least 1 major postoperative complication, the likelihood of death was still negatively associated with BMI. This negative association of mortality with BMI was observed despite the higher prevalence of chronic diseases, such as hypertension, diabetes, and dyspnea at rest, in the increasing BMI classes.

Controversy remains regarding the association between BMI and mortality, in particular about the shape of the curve for the association between BMI and mortality. Epidemiologic studies have variously described J‐shaped, U‐shaped, monotonic, or linear relationships.16, 17 In the surgical population, a reverse J‐shaped relationship between BMI category and mortality has been described.18, 19 Sometimes this is referred to as obesity paradox or reverse epidemiology: a trend whereby overweight and moderately obese patients have better outcomes and lower risk of death than leaner patients.18 This phenomenon is particularly well described in adult20 and elderly heart failure and hypertensive patients.21 Many of these studies either had very few minority patients,21 or mortality pattern was not analyzed along ethnic lines.

Few studies10 have focused exclusively on minority surgical patients. Some investigators have determined that high BMI in black adults may not be as important a risk factor for mortality6, 7 as in whites. Our data suggest that among minority surgical patients, the relationship appeared to be a downward trend in mortality from low to high BMI, thus revealing the obesity paradox. This pattern was evident even in patients who developed 1 major complication in the postoperative period, suggesting that high BMI also protects against failure to rescueor death after a major complication.

Despite decades of research, the mechanisms underlying the obesity paradox remain speculative.20, 22. Many have posited that adiposity may confer protection against cytokines and various inflammatory mediators in heart failure patients by the production of buffering lipoproteins.23, 24 It is conceivable that similar protection against inflammatory response to surgical tissue trauma is operational in minority patients with high BMI. Another possible reason for the obesity paradox is the clinical presentation and disease progression at the time of surgery. Perhaps, similar to the observation in obese patients with heart failure,25 obese minority patients are symptomatic at an earlier stage of their disease than lean patients, making for earlier diagnosis and treatment. Thus, obesity may simply be a marker of less severe disease at the time of presentation.

Obese patients may also be more aggressively monitored and treated in the perioperative period than lean patients, because of the general perception that they are a high‐risk group.10 This may partly explain the decreased likelihood of failure to rescue with increasing BMI in our patients. Increased vigilance and prompt treatment of complications should reduce the overall morbidity and mortality rate in this group. It is also conceivable that a therapeutic selection bias is operational in the patients we studied. This describes scenarios where relatively healthy obese minority patients were operated upon, while sicker, morbidly obese patients were denied surgery due to perceived prohibitive risks. However, we would have expected a higher proportion of severely obese patients to present for emergency surgery, which is contrary to our finding of the lowest incidence of emergency surgery in the severely obese group. It is also possible that severe obesity may be associated with a higher attrition rate, such that the extremely obese patients did not live long enough to present for surgery. This is somewhat likely, given the significantly younger age of the severely obese patients in our study cohort. It is, however, impossible to determine survival effect from a cross‐sectional hospital‐based study design. Clearly, mechanisms used to explain the obesity paradox in minority surgical patients are likely to remain speculative, owing to the interaction of several factors such as concomitant comorbidities, disease progression at the time of presentation, patients' weight history, and regional fat distribution.

The current study confirms the findings of previous investigators26 about the importance of reducing major postoperative complications in surgical patients. While this may seem axiomatic, it deserves reiteration because the risk of postoperative mortality increases considerably in all the BMI categories following 1 or more major postoperative complication. However, it is not clear why obese and morbidly obese patients had a lower incidence of failure to rescue. This may be related to greater physiologic reserve in the obese and morbidly obese group, especially because patients in the higher BMI groups were significantly younger than the normal weight or lean patients. For the same reason, these younger, severely obese patients may have been more aggressively monitored and treated, thereby increasing the likelihood of being rescued following a major complication. It is also possible that the lower proportion of emergency procedures performed in obese and severely obese groups was somewhat protective, especially because emergency surgery was an independent predictor of overall mortality in this cohort of patients. In fact, when we stratified the patients according to urgency of surgery and explored the bivariate relationship between BMI category and mortality (data not shown) among those undergoing urgent surgery, the geometrical distribution of mortality did show a reverse‐J pattern with the highest proportion of cases in the underweight group, declining in the normal BMI and overweight group, and increasing steadily in obese and severely obese group. To this end, caution should be exercised when interpreting the association of BMI group with postoperative mortality for procedures performed as an emergency.

Smoking and antecedent illness are 2 confounding factors commonly criticized in studies attempting to associated BMI with mortality. This is because smokers tend to weigh less and have higher mortality rates than nonsmokers. The present investigation did not find a significant contribution of smoking to mortality when other factors included in a logistic regression model were considered. The current study's findings are consistent with those of previous data in African American patients,27 and contrasts with the excess mortality described in currently smoking Caucasian men and women.28 It is possible that smoking is not an important effect modifier when considering the relevance of BMI to postoperative mortality in minority patients.

Obesity affects all segments of the American population. However, it imposes a larger burden and poses a greater threat to minority populations.1 The increase in overall prevalence of obesity and obesity‐related diseases are especially pronounced in ethnic minorities,2 and the outlook for minorities who develop obesity‐associated diseases such as stroke and chronic renal disease is worse than in their Caucasian counterparts.3

Despite the higher prevalence of obesity in ethnic minorities, the majority of research on the relationship between body mass index (BMI) and mortality has been conducted among Caucasians in the United States. This is due largely to the small number of minority participants in most studies, which makes for low statistical power.4

A curious epidemiologic paradox has been the observation, in many studies, that black adults have lower morbidity and mortality associated with obesity compared to Caucasians.5 In fact, some authors suggest that high BMI among black and other minorities may not be as strong a risk factor for mortality as it is in others.6, 7

Very few studies have specifically examined the contribution of BMI to postoperative outcome in a large cohort of minority patients.8, 9 Similarly, the authors are unaware of any previous studies describing the clinical relevance of being overweight and obese in minority patients undergoing surgery. Therefore, the primary objective of this observational study was to describe the prevalence of overweight and obesity in a large cohort of minority surgical patients, and the impact of BMI class on their postoperative outcome. Our a priori hypothesis was that obese minority surgical patients would have a poorer postoperative outcome and have higher 30‐day all‐cause mortality than normal weight individuals.

METHODS

Study data were derived from the Participant Use Data File of the American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP) for the calendar years 2005 to 2008. This multi‐institutional (186 participating centers) reporting system was designed to provide risk‐adjusted surgical outcome data from throughout the United States.

The methodology for collecting these data, including their accuracy and reproducibility, has been detailed in previous publications.10, 11 It is briefly reviewed here. Dedicated nurse clinical reviewers at each hospital prospectively enrolled patients and collected data in a standardized fashion according to strict ACS‐NSQIP definitions. A systematic sample was obtained by taking the first 40 cases per nurse reviewer on an 8‐day cycle from the operating room log, ensuring that no particular operating room day block time would bias the weighting of cases. Nurse reviewers had completed comprehensive training regarding definitions and data extraction, as well as continuing education and monitoring through the ACS‐NSQIP program. They are assessed for inter‐rater reliability during biennial site visits. Information was obtained from patient medical records, physician office records, and telephone interviews. Patients were followed through their hospital course and after discharge from hospital up to 30 days postoperatively. A high level of accuracy and reproducibility of the data have been previously demonstrated.12

Race was defined as African American, Hispanic, Asian or Pacific Islander, or American Indian/Alaskan native, as identified by the clinical care provider, or within the medical record. Patients were excluded if race was coded as white, or not recorded. We also excluded patients with missing record of height and/or weight. The final study cohort consisted of 119,619 minority patients. We then computed BMI as weight in kilograms divided by the square of the height in meters (BMI = kg/m²). Patients were classified as underweight (BMI 18.5 kg/m²), normal weight (BMI = 18.6‐24.9 kg/m²), overweight (BMI = 25‐29.9 kg/m²), obese (BMI = 30‐39.9 kg/m²), and morbidly obese (BMI 40 kg/m²) in accordance with National Institute of Health (NIH) standards.13

RESULTS

The study cohort included 119,619 surgical patients (Table 1). Their mean (standard deviation [SD]) age was 50.4 (16.9), and the mean (SD) BMI of 30.3 (8.9) kg/m² was in the obese range. The overall prevalence of high BMI (overweight or obese) was 70.8%. A very small proportion, 2.7%, of patients was classified as underweight. Sex‐stratified demographic and behavioral characteristics differed significantly across all the variables in our study cohort. Men were more likely to be overweight, whereas women were more likely to be obese or severely obese. A majority (77.4%) of the patients were non‐elderly adults (<65years) undergoing elective (85.9%) surgical procedures. The minority patients in this study were African American (50%), Hispanic (36%), Asian and Pacific Islander (10%), and American Indian and Alaskan native (4%).

The distribution of baseline preoperative clinical characteristics by BMI class revealed many significant differences (Table 2). Age was significantly different among the BMI classes, with the severely obese group being about 8 years younger than the underweight or normal weight group. Similarly, severely obese patients were more likely to be women, less likely to smoke, more likely to be hypertensive, diabetic, have a history of dyspnea at rest, and more likely to belong to high ASA class. On the other hand, underweight patients were more likely to have disseminated cancer, be current smokers, consume more than 2 alcoholic drinks per day, have active chronic obstructive pulmonary disease (COPD), and have ascites. They were also more likely to be on dialysis and have cardiac disease, as well as a history of stroke. Urgency of surgery also varied significantly across the BMI categories, with the underweight group having the highest incidence of emergency surgery (20.6%) and the severely obese group being the least likely to present for emergency surgery (8.2%).

Perioperative outcomes according to BMI classes documented significant differences (Table 3). Work relative value unit (Work RVU, a measure of surgical complexity), as well as total anesthesia and operation time decreased in a stepwise fashion across the BMI classes to the obese group, followed by increase in these parameters in the severely obese group. Following a decrease to the normal BMI category, there was a positive association between BMI and the incidence of postoperative superficial and deep wound infection, as well as wound disruption.

There was a negative association between BMI class and the likelihood of postoperative sepsis, septic shock, reintubation, delayed ventilator wean, and postoperative pneumonia. Similarly, the proportions of patients who developed postoperative acute renal failure, cardiac arrest, and those who required postoperative blood transfusion or needed reoperation, decreased significantly across the BMI classes, with the highest proportion of cases being in the underweight group and the lowest in the severely obese group. Overall composite morbidity was twice as high in the underweight compared to the severely obese group.

There were 1758 deaths among the study's 119,619 patients, resulting in an overall mortality rate of 1.5%. The overall major complication rate was 13.8%. The distribution of total mortality rate as well as mortality in patients with at least 1 major postoperative complication across BMI classes revealed consistent differences (Figure 1). Over the entire range of BMI classes, there was a progressive, stepwise decrease in the proportion of deaths with increasing BMI. This pattern also occurred among patients who developed at least 1 major postoperative complication, indicating a reduced likelihood of death after a major complication. This is reflective of a reduced likelihood of death after a major complication (failure to rescue) with increasing BMI.

Figure 1

Multivariate logistic regression defined a number of factors associated with 30‐day mortality (Table 4). The Hosmer and Lemeshow goodness‐of‐fit test for this model was not statistically significant (² = 17.8, df = 8, P = 0.23). High ASA physical status was associated with high odds of mortality. Specifically, when controlling for the other covariates in the model, ASA status was associated with a 5‐fold increased relative odds of death (adjusted odds ratio [OR] = 5.30; 95% confidence interval = 4.96‐5.79, P < 0.001). Similarly, occurrence of 1 or more major postoperative complication was associated with 6‐fold increased relative odds of mortality. The paradoxical effect of BMI category observed on univariate analysis was maintained in the multivariate model. Specifically, underweight patients had the highest relative odds of mortality, while severely obese patients had the lowest, compared with patients at a healthy weight (Table 4). Interestingly, smoking had no significant effect on the odds of mortality after controlling for other factors. Similarly, the specific racial group and the timing of the surgical intervention had no significant effect on mortality.

DISCUSSION

In this large, study of minority surgical patients, the impact of BMI on the 30‐day morbidity and mortality was unexpected. The working hypothesis was that overweight and obese patients would have a worse outcome after surgery. However, contrary to this hypothesis, the lowest all‐cause mortality rate was found in the severely obese (BMI 40 kg/m²) group in both men and women. Death rates decreased progressively in a stepwise fashion from the underweight to the severely obese group. Similarly, even in patients who developed at least 1 major postoperative complication, the likelihood of death was still negatively associated with BMI. This negative association of mortality with BMI was observed despite the higher prevalence of chronic diseases, such as hypertension, diabetes, and dyspnea at rest, in the increasing BMI classes.

Controversy remains regarding the association between BMI and mortality, in particular about the shape of the curve for the association between BMI and mortality. Epidemiologic studies have variously described J‐shaped, U‐shaped, monotonic, or linear relationships.16, 17 In the surgical population, a reverse J‐shaped relationship between BMI category and mortality has been described.18, 19 Sometimes this is referred to as obesity paradox or reverse epidemiology: a trend whereby overweight and moderately obese patients have better outcomes and lower risk of death than leaner patients.18 This phenomenon is particularly well described in adult20 and elderly heart failure and hypertensive patients.21 Many of these studies either had very few minority patients,21 or mortality pattern was not analyzed along ethnic lines.

Few studies10 have focused exclusively on minority surgical patients. Some investigators have determined that high BMI in black adults may not be as important a risk factor for mortality6, 7 as in whites. Our data suggest that among minority surgical patients, the relationship appeared to be a downward trend in mortality from low to high BMI, thus revealing the obesity paradox. This pattern was evident even in patients who developed 1 major complication in the postoperative period, suggesting that high BMI also protects against failure to rescueor death after a major complication.

Despite decades of research, the mechanisms underlying the obesity paradox remain speculative.20, 22. Many have posited that adiposity may confer protection against cytokines and various inflammatory mediators in heart failure patients by the production of buffering lipoproteins.23, 24 It is conceivable that similar protection against inflammatory response to surgical tissue trauma is operational in minority patients with high BMI. Another possible reason for the obesity paradox is the clinical presentation and disease progression at the time of surgery. Perhaps, similar to the observation in obese patients with heart failure,25 obese minority patients are symptomatic at an earlier stage of their disease than lean patients, making for earlier diagnosis and treatment. Thus, obesity may simply be a marker of less severe disease at the time of presentation.

Obese patients may also be more aggressively monitored and treated in the perioperative period than lean patients, because of the general perception that they are a high‐risk group.10 This may partly explain the decreased likelihood of failure to rescue with increasing BMI in our patients. Increased vigilance and prompt treatment of complications should reduce the overall morbidity and mortality rate in this group. It is also conceivable that a therapeutic selection bias is operational in the patients we studied. This describes scenarios where relatively healthy obese minority patients were operated upon, while sicker, morbidly obese patients were denied surgery due to perceived prohibitive risks. However, we would have expected a higher proportion of severely obese patients to present for emergency surgery, which is contrary to our finding of the lowest incidence of emergency surgery in the severely obese group. It is also possible that severe obesity may be associated with a higher attrition rate, such that the extremely obese patients did not live long enough to present for surgery. This is somewhat likely, given the significantly younger age of the severely obese patients in our study cohort. It is, however, impossible to determine survival effect from a cross‐sectional hospital‐based study design. Clearly, mechanisms used to explain the obesity paradox in minority surgical patients are likely to remain speculative, owing to the interaction of several factors such as concomitant comorbidities, disease progression at the time of presentation, patients' weight history, and regional fat distribution.

The current study confirms the findings of previous investigators26 about the importance of reducing major postoperative complications in surgical patients. While this may seem axiomatic, it deserves reiteration because the risk of postoperative mortality increases considerably in all the BMI categories following 1 or more major postoperative complication. However, it is not clear why obese and morbidly obese patients had a lower incidence of failure to rescue. This may be related to greater physiologic reserve in the obese and morbidly obese group, especially because patients in the higher BMI groups were significantly younger than the normal weight or lean patients. For the same reason, these younger, severely obese patients may have been more aggressively monitored and treated, thereby increasing the likelihood of being rescued following a major complication. It is also possible that the lower proportion of emergency procedures performed in obese and severely obese groups was somewhat protective, especially because emergency surgery was an independent predictor of overall mortality in this cohort of patients. In fact, when we stratified the patients according to urgency of surgery and explored the bivariate relationship between BMI category and mortality (data not shown) among those undergoing urgent surgery, the geometrical distribution of mortality did show a reverse‐J pattern with the highest proportion of cases in the underweight group, declining in the normal BMI and overweight group, and increasing steadily in obese and severely obese group. To this end, caution should be exercised when interpreting the association of BMI group with postoperative mortality for procedures performed as an emergency.

Smoking and antecedent illness are 2 confounding factors commonly criticized in studies attempting to associated BMI with mortality. This is because smokers tend to weigh less and have higher mortality rates than nonsmokers. The present investigation did not find a significant contribution of smoking to mortality when other factors included in a logistic regression model were considered. The current study's findings are consistent with those of previous data in African American patients,27 and contrasts with the excess mortality described in currently smoking Caucasian men and women.28 It is possible that smoking is not an important effect modifier when considering the relevance of BMI to postoperative mortality in minority patients.