Rickey E. Carter

2012 provisional classification criteria for polymyalgia rheumatica: a European League Against Rheumatism/American College of Rheumatology collaborative initiative

The objective of this study was to develop EULAR/ACR classification criteria for polymyalgia rheumatica (PMR). Candidate criteria were evaluated in a 6-month prospective cohort study of 125 patients with new onset PMR and 169 non-PMR comparison subjects with conditions mimicking PMR. A scoring algorithm was developed based on morning stiffness >45 minutes (2 points), hip pain/limited range of motion (1 point), absence of RF and/or ACPA (2 points), and absence of peripheral joint pain (1 point). A score ≥4 had 68% sensitivity and 78% specificity for discriminating all comparison subjects from PMR. The specificity was higher (88%) for discriminating shoulder conditions from PMR and lower (65%) for discriminating RA from PMR. Adding ultrasound, a score ≥5 had increased sensitivity to 66% and specificity to 81%. According to these provisional classification criteria, patients ≥50 years old presenting with bilateral shoulder pain, not better explained by an alternative pathology, can be classified as having PMR in the presence of morning stiffness>45 minutes, elevated CRP and/or ESR and new hip pain. These criteria are not meant for diagnostic purposes.

Intravenous Contrast Material–induced Nephropathy: Causal or Coincident Phenomenon?

PURPOSE To determine the causal association and effect of intravenous iodinated contrast material exposure on the incidence of acute kidney injury (AKI), also known as contrast material-induced nephropathy (CIN). MATERIALS AND METHODS This retrospective study was approved by an institutional review board and was HIPAA compliant. Informed consent was waived. All contrast material-enhanced (contrast group) and unenhanced (noncontrast group) abdominal, pelvic, and thoracic CT scans from 2000 to 2010 were identified at a single facility. Scan recipients were sorted into low- (<1.5 mg/dL), medium- (1.5-2.0 mg/dL), and high-risk (>2.0 mg/dL) subgroups of presumed risk for CIN by using baseline serum creatinine (SCr) level. The incidence of AKI (SCr ≥ 0.5 mg/dL above baseline) was compared between contrast and noncontrast groups after propensity score adjustment by stratification, 1:1 matching, inverse weighting, and weighting by the odds methods to reduce intergroup selection bias. Counterfactual analysis was used to evaluate the causal relation between contrast material exposure and AKI by evaluating patients who underwent contrast-enhanced and unenhanced CT scans during the study period with the McNemar test. RESULTS A total of 157,140 scans among 53,439 unique patients associated with 1,510,001 SCr values were identified. AKI risk was not significantly different between contrast and noncontrast groups in any risk subgroup after propensity score adjustment by using reported risk factors of CIN (low risk: odds ratio [OR], 0.93; 95% confidence interval [CI]: 0.76, 1.13; P = .47; medium risk: odds ratio, 0.97; 95% CI: 0.81, 1.16; P = .76; high risk: OR, 0.91; 95% CI: 0.66, 1.24; P = .58). Counterfactual analysis revealed no significant difference in AKI incidence between enhanced and unenhanced CT scans in the same patient (McNemar test: χ(2) = 0.63, P = .43) (OR = 0.92; 95% CI: 0.75, 1.13; P = .46). CONCLUSION Following adjustment for presumed risk factors, the incidence of CIN was not significantly different from contrast material-independent AKI. These two phenomena were clinically indistinguishable with established SCr-defined criteria, suggesting that intravenous iodinated contrast media may not be the causative agent in diminished renal function after contrast material administration. SUPPLEMENTAL MATERIAL http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.12121823/-/DC1.

Combining Body Mass Index With Measures of Central Obesity in the Assessment of Mortality in Subjects With Coronary Disease : Role of “Normal Weight Central Obesity”

OBJECTIVES This study sought to assess the mortality risk of patients with coronary artery disease (CAD) based ona combination of body mass index (BMI) with measures of central obesity. BACKGROUND In CAD patients, mortality has been reported to vary inversely with BMI (“obesity paradox”). In contrast,central obesity is directly associated with mortality. Because of this bidirectionality, we hypothesized that CAD patients with normal BMI but central obesity would have worse survival compared to individuals with other combinations of BMI and central adiposity. METHODS We included 15,547 participants with CAD who were part of 5 studies from 3 continents. Multivariate stratifiedCox-proportional hazard models adjusted for potential confounders were used to assess mortality risk according to different patterns of adiposity that combined BMI with measures of central obesity. RESULTS Mean age was 66 years, 60% were men. There were 5,507 deaths over a median follow-up of 2.4 years (IQR: 0.5 to 7.4 years). Individuals with normal weight central obesity had the worst long-term survival: a person with BMI of 22 kg/m2 and waist circumference (WC) of 101 cm had higher mortality than a person with similar BMI but WC of 85 cm (HR: 1.10[95% CI: 1.05 to 1.17]), than a person with BMI of 26 kg/m2 and WC of 85 cm (HR: 1.20 [95% CI: 1.09 to 1.31]), than a person with BMI of 30 kg/m2 and WC of 85 cm (HR: 1.61 [95% CI: 1.39 to 1.86]) and than a person with BMI of 30kg/m2 and WC of 101 cm (HR: 1.27 [95% CI: 1.18 to 1.39), p < 0.0001 for all). CONCLUSIONS In patients with CAD, normal weight with central obesity is associated with the highest risk of mortality [corrected].

Continuous Oximetry/Capnometry Monitoring Reveals Frequent Desaturation and Bradypnea During Patient-Controlled Analgesia

BACKGROUND:The most serious complication of patient-controlled analgesia (PCA) is respiratory depression (RD). The incidence of RD in the literature is derived from intermittent sampling of pulse oximetry (Spo2) and respiratory rate and defined as a deviation below an arbitrary threshold. METHODS:We monitored postsurgical patients in a hospital ward receiving morphine or meperidine PCA with continuous oximetry and capnography. Nurses responding to audible monitor bedside alarms documented respiratory status and interventions. RESULTS:A total of 178 patients were included in the analysis, 12% and 41% of whom had episodes of desaturation (Spo2 <90%) and bradypnea (respiratory rate <10) lasting 3 min or more. One patient required “rescue” with positive pressure ventilation, and none required naloxone. Patients over 65 years of age and the morbidly obese were at greater risk for desaturation. Patients over 65 years of age were also more likely to have bradypnea, whereas the morbidly obese and patients receiving continuous infusions were less likely to have bradypnea. CONCLUSIONS:Our incidence of RD by bradypnea is significantly higher than the 1%–2% incidence in the literature, using the same threshold criteria but more stringent duration criteria, while our incidence of RD based on desaturation is consistent with previous estimates. We conclude that continuous respiratory monitoring is optimal for the safe administration of PCA, because any RD event can progress to respiratory arrest if undetected. Better alarm algorithms must be implemented to reduce the frequent alarms triggered by threshold criteria for RD.

Risk of Intravenous Contrast Material–mediated Acute Kidney Injury: A Propensity Score–matched Study Stratified by Baseline-estimated Glomerular Filtration Rate

PURPOSE To determine the effect of baseline estimated glomerular filtration rate (eGFR) on the causal association between intravenous iodinated contrast material exposure and subsequent development of acute kidney injury (AKI) in propensity score-matched groups of patients who underwent contrast material-enhanced or unenhanced computed tomography (CT). MATERIALS AND METHODS This retrospective study was HIPAA compliant and institutional review board approved. All patients who underwent contrast-enhanced (contrast material group) or unenhanced (non-contrast material group) CT between 2000 and 2010 were identified and stratified according to baseline eGFR by using Kidney Disease Outcomes Quality Initiative cutoffs for chronic kidney disease into subgroups with eGFR of 90 or greater, 60-89, 30-59, and less than 30 mL/min/1.73 m(2). Propensity score generation and 1:1 matching of patients were performed in each eGFR subgroup. Incidence of AKI (serum creatinine [SCr] increase of ≥0.5 mg/dL [≥44.2 μmol/L] above baseline) was compared in the matched subgroups by using the Fisher exact test. RESULTS A total of 12 508 propensity score-matched patients with contrast-enhanced and unenhanced scans met all inclusion criteria. In this predominantly inpatient cohort, the incidence of AKI significantly increased with decreasing baseline eGFR (P < .0001). However, this incidence was not significantly different between contrast material and non-contrast material groups in any eGFR subgroup; for the subgroup with eGFR of 90 or greater (n = 1642), odds ratio (OR) was 0.91 (95% confidence interval [CI]: 0.38, 2.15), P = .82; for the subgroup with eGFR of 60-89 (n = 3870), OR was 1.03 (95% CI: 0.66, 1.60), P = .99; for the subgroup with eGFR of 30-59 (n = 5510), OR was 0.94 (95% CI: 0.76, 1.18), P = .65; and for the subgroup with eGFR of less than 30 mL/min/1.73 m(2) (n = 1486), OR was 0.97 (95% CI: 0.72, 1.30), P = .89. CONCLUSION Diminished eGFR is associated with an increased risk of SCr-defined AKI following CT examinations. However, the risk of AKI is independent of contrast material exposure, even in patients with eGFR of less than 30 mL/min/1.73 m(2).

A prospective study of health and risk of mortality after spinal cord injury.

OBJECTIVE To test hypothesized relationships between multiple health parameters and mortality among persons with spinal cord injury (SCI) while controlling for variations in biographical and injury characteristics. DESIGN Prospective cohort study with health data collected in late 1997 and early 1998 and mortality status ascertained in December 2005. SETTING A large rehabilitation hospital in the Southeastern United States. PARTICIPANTS A total of 1389 adults with traumatic SCI, at least 1 year postinjury. INTERVENTIONS Not applicable. MAIN OUTCOME MEASURES The primary outcome was time from survey to mortality (or time of censoring). Mortality status was determined using the National Death Index and the Social Security Death Index. There were 225 deaths (16.2%) by December 31, 2005. RESULTS Cox proportional hazards modeling identified several significant health predictors of mortality status, while controlling for biographic and injury factors. Two sets of analyses were conducted--the first identifying the significance of a single variable of interest and the second analysis building a comprehensive model based on an optimal group of variables. Multiple types of health conditions were associated with mortality. The best set of health predictors included probable major depression, surgeries to repair pressure ulcers, fractures and/or amputations, symptoms of infections, and days hospitalized. Inclusion of these variables, along with a general health rating, improved prediction of survival compared with biographic and injury variables alone, because the pseudo R(2) increased from .12 to .18 and the concordance from .730 to .776. CONCLUSIONS In addition to secondary conditions that have been the traditional focus of prevention efforts (eg, pressure ulcers, urinary tract infections), amputations, fractures, and depressive symptoms were associated with higher risk for mortality; however, further research is needed to identify the association of specific conditions with causes of death and to determine whether interventions can modify these conditions and ultimately improve survival.

Complications following 573 Percutaneous Renal Radiofrequency and Cryoablation Procedures

PURPOSE To review complications related to percutaneous renal tumor ablation. MATERIALS AND METHODS Prospectively collected data related to renal radiofrequency (RF) ablation and cryoablation procedures performed from May 2000 through November 2010 were reviewed. This included 573 renal ablation procedures performed in 533 patients to treat 633 tumors. A total of 254 RF ablation and 311 cryoablation procedures were performed; eight patients underwent simultaneous RF ablation and cryoablation. The mean age of patients at the time of the procedure was 70 years (range, 24-93 y), and 382 of 573 procedures (67%) were performed in male patients. Complications were recorded according to the Clavien-Dindo classification scheme. Duration of hospitalization was also documented. RESULTS Of the 573 procedures, 63 produced complications (11.0% overall complication rate). There were 66 reported complications, of which 38 (6.6% of total procedures) were Clavien-Dindo grade II-IV major complications; there were no deaths. Major complication rates did not differ statistically (P = .15) between cryoablation (7.7%; 24 of 311) and RF ablation (4.7%; 12 of 254). Of the complications related to cryoablation, bleeding and hematuria were most common. Bleeding during cryoablation was associated with advanced age, increased tumor size, increased number of cryoprobes, and central position (P < .05). Of those treated with RF ablation, nerve and urothelial injury were most common. Mean hospitalization duration was 1 day for RF ablation and cryoablation. CONCLUSIONS Complications related to percutaneous renal ablation are infrequent. Recognition of potential complications and associated risk factors can allow optimization of periprocedural care.

Small (<4 cm) Renal Mass: Differentiation of Angiomyolipoma without Visible Fat from Renal Cell Carcinoma Utilizing MR Imaging

PURPOSE To determine whether a combination of magnetic resonance (MR) parameters can help differentiate small angiomyolipomas (AMLs) without visible fat from renal cell carcinomas (RCCs). MATERIALS AND METHODS This HIPAA-compliant retrospective study received institutional review board approval; 69 men and 42 women (mean age, 59.7 years) with 15 AMLs without visible fat and 104 RCCs underwent MR. The development set consisted of 10 AMLs and 71 RCCs; the validation set consisted of five AMLs and 33 RCCs. T1-weighted fast spin-echo (SE), fat-suppressed T2-weighted fast SE, in- and opposed-phase gradient-echo (GRE), and fat-suppressed three-dimensional T1-weighted spoiled GRE sequences were performed before and after contrast material administration. Tumor signal intensity (SI) was measured. T1 and T2 SI ratio (ratio of tumor to renal cortex SI on T1- and T2-weighted images, respectively), SI index (SII) ([SI(in) 2 SI(opp)]/[SI(in)] × 100; SI(in) and SI(opp) are tumor SI on in- and opposed-phase images, respectively), and arterial-to-delayed enhancement ratio ([SI(art) 2 SI(pre)]/[SI(del) 2 SI(pre)]; SI(pre), SI(art), and SI(del) are tumor SI on unenhanced, arterial phase, and delayed phase three-dimensional T1-weighted spoiled GRE images, respectively) were compared. Combinations of MR parameter threshold levels were constructed from development set and validated with validation set. Sensitivity, specificity, and accuracy for differentiating between AML and RCC were calculated for combinations of MR parameter threshold levels. RESULTS AML had significantly higher T1 SI ratio (P = .04), lower T2 SI ratio (P = .001), higher SII (P = .02), and higher arterial-to-delayed enhancement ratio (P < .001) than RCC. Sensitivity, specificity, and accuracy for combination of T2 SI ratio less than 0.9 and ([SII greater than 20% and T1 SI ratio greater than 1.2] or arterial-to-delayed enhancement ratio greater than 1.5) were 73% (11 of 15), 99% (103 of 104), and 96% (114 of 119), respectively, for differentiating AML from RCC. CONCLUSION A combination of T2 SI ratio less than 0.9 and ([SII greater than 20% and T1 SI ratio greater than 1.2] or arterial-to-delayed enhancement ratio greater than 1.5) was accurate in differentiating AML from RCC.

Normal-Weight Central Obesity: Implications for Total and Cardiovascular Mortality

Context It is uncertain whether measures of central obesity, such as waist-to-hip ratio (WHR), provide additional information beyond body mass index (BMI) in defining mortality risks associated with obesity. Contribution This population-based cohort study found that normal BMI and central obesity (defined by WHR) were associated with the worst long-term survival compared with individuals with normal fat distribution regardless of BMI category. Caution Information on body fat distribution was based on anthropometric indicators alone. Implication Normal weight with central obesity may represent an important group for targeted lifestyle modifications and other preventive strategies. Obesity defined by body mass index (BMI) or measures of central obesity, such as waist-to-hip ratio (WHR) and waist circumference, is associated with increased total and cardiovascular mortality (13). However, a recent meta-analysis (4) showed that being overweight according to BMI was actually associated with lower total mortality, challenging the paradigm that BMI is linked to increased mortality. Further, whether measures of fat distribution provide any incremental risk information beyond BMI alone has been a major source of controversy (2, 3, 58). Indeed, the 2013 American Heart Association/American College of Cardiology/The Obesity Society guideline for the management of obesity (9) does not recommend measuring WHR and assumes that persons with normal BMI are not exposed to any obesity-related cardiovascular risk in view of the limited available data proving otherwise. A recent large study (6) showed that incorporating waist circumference information in prediction models did not increase the prognostic value already provided by BMI; however, for a given BMI category, subgroups of waist circumference or WHR were also associated with increased mortality risk. Other studies showed that measures of central obesity, such as WHR, waist-to-height ratio (10, 11), or waist circumference alone, may provide additional information beyond BMI on mortality risk among middle-aged adults, provided there is no adjustment for obesity-related cardiovascular risk factors (2, 3, 7). Further, a study (12) has shown that measures of central obesity are more strongly associated with total and cardiovascular disease mortality rates than BMI. Another study (13) showed that persons with normal body weight measured by BMI, but who had increased body fat measured by bioimpedance, have higher total and cardiovascular mortality rates and a higher prevalence of metabolic syndrome and its components than those with normal BMI and body fat content. In addition, a recent meta-analysis of individual-patient data in those with coronary artery disease (12) has shown that persons with normal BMI who are in the top tertile of central obesity measures had the highest total mortality rate. These results have been attributed to several factors. First, the diagnostic accuracy of BMI for obesity is not optimal, especially in persons with greater body fat percentages and normal or intermediate BMI (14). Second, those with normal body weight and higher body fat have less muscle mass, which is a factor associated with higher mortality risk and metabolic dysregulation (15, 16). Third, animal and human studies (17) have recently shown that adipose tissue in the legs and buttocks may have a favorable effect on glucose metabolism. Finally, persons with a central distribution of fat, particularly when measured with WHR, have less adipose tissue in the lower extremities (17). To our knowledge, no studies in the general U.S. population have specifically focused on assessing the mortality risk in persons with normal BMI and central obesity compared with those who are overweight or obese according to BMI. Thus, we hypothesized that persons with normal BMI and central obesity would have greater mortality risk than those who have any other combination of BMI and central obesity. We investigated the total and cardiovascular mortality risks associated with different patterns of body adiposity in a large cohort of participants in NHANES III (Third National Health and Nutrition Examination Survey) (1988 to 1994). Because hip circumference was not measured in the most recent National Health and Nutrition Examination Surveys (conducted yearly from 1999 to 2010) and WHR data to define central obesity were crucial to our primary hypothesis, we have used data from NHANES III instead. Methods Study Design and Participants NHANES III is a cross-sectional survey that produces generalizable health estimates for the U.S. population using a stratified, multistage, probability sampling design. From a sample of 39695 persons, 33994 were interviewed and 30818 were examined at mobile examination centers. The examination consisted of extensive anthropometric, physiologic, and laboratory testing. Waist and hip circumferences were measured by a trained examiner with a measuring tape positioned at the high point of the iliac crest for the waist and at the greatest circumference of the buttocks. The design and methods for the survey are available elsewhere (18). In our study, 16124 adults aged 18 years or older had WHRs available. Because extremely thin persons and those with a history of nonskin cancer have a higher mortality risk, we further restricted our analysis to persons with a BMI greater than 18.5 kg/m2 and those without a history of nonskin cancer. The resulting sample was 15184 participants (7249 men and 7935 women). Total and Cardiovascular Mortality Assessment Identifier data were matched to the National Death Index to determine mortality status, with mortality follow-up from the date of the NHANES survey through 31 December 2006. A complete description of the methodology to link baseline NHANES III data to the National Death Index can be found elsewhere (19). International Classification of Diseases, Ninth Revision (ICD-9), codes from 1986 to 1998 and International Classification of Diseases, 10th Revision (ICD-10), codes from 1999 to 2000 were used to ascertain the underlying cause of death. Cardiovascular deaths were defined as those with ICD-9 codes 390 to 398, 402, and 404 to 429 and ICD-10 codes I00 to I09, I11, I13, and I20 to I51 (NHANES III codes 53 to 75). Statistical Analysis The overarching analytic goal was to estimate the influence of various magnitudes of central obesity and BMI on total mortality. To do this, we conducted weighted survival modeling that enabled the estimation of the relative risk for mortality, quantified by the hazard ratio (HR), and the expected survival for NHANES III participants. The NHANES III survey design and sampling weights were incorporated into the statistical analysis to calculate weighted means, SEs for continuous variables, and weighted percentages for categorical variables. To determine the total mortality associated with the different patterns of adiposity, we created multivariable Cox proportional hazards models and adjusted for potential confounders previously shown to be associated with obesity and mortality (4). These variables were age at examination, sex, education level, and smoking history. Although we considered adjusting for obesity-related cardiovascular risk factors in the models, we did not adjust our final estimates for these factors. Epidemiologic obesity research has shown that it might be inappropriate to control for factors in the causal pathway between obesity and death, such as diabetes, atherogenic dyslipidemia, and hypertension. In testing for differences in mortality risk for combinations of central obesity (defined by WHR) and BMI, we considered higher-order interactions of WHR with BMI and other covariates. The association pattern of WHR and BMI was found to be different for men versus women (that is, statistically significant higher-order interaction terms), so the final modeling was conducted using sex-stratified data to more clearly present the findings. The interaction terms allowed the potential quadratic risks (U-shaped risks) of values for these variables. The estimated model contains polynomial functions of BMI and WHR (for example, BMI2 and BMI2WHR2). These terms allow for relationships that are more sensitive to change in risk for mortality based on unique combinations (profiles) of WHR and BMI. The estimated risk function, when other covariates in the model are controlled for, will resemble a saddle with high- and low-risk areas. When possible, covariates were the grand mean centered to lessen the collinearity induced from quadratic effects. Likelihood ratio tests were used to determine whether these higher-order model terms could be removed. The proportional hazards assumption for all variables was assessed and satisfied for the final models. After these models were established, we estimated HRs with estimated model variables for different combinations of WHR and BMI stratified by sex. For these comparisons, we chose a BMI of 22 kg/m2 to represent persons with normal BMI, 27.5 kg/m2 to represent overweight persons, and 33 kg/m2 to represent obese persons. For WHR, we chose 0.89 and 1.00 for men and 0.80 and 0.92 for women as a measure of central obesity. Each of these sets of values were chosen either to reflect the approximate midpoint of standard clinical interpretationsto avoid issues with values at common thresholds (for example, BMI values at 30 kg/m2)or to be clinical targets we sought to better understand. Wald-based (or large sample-based) HR estimates and their SEs were assessed to provide significance tests among these representative patient profiles (20). Once the fitted Cox model was deemed satisfactory, we sought to estimate measures of absolute risk by means-adjusted 5- and 10-year survival estimates (21). In this analysis, we replicated observations to standardize (reweight) them and ensure balance across sex, age, WHR, and BMI categories. The expected survival was computed as a weighted estimate

Normal-weight central obesity

Context It is uncertain whether measures of central obesity, such as waist-to-hip ratio (WHR), provide additional information beyond body mass index (BMI) in defining mortality risks associated with obesity. Contribution This population-based cohort study found that normal BMI and central obesity (defined by WHR) were associated with the worst long-term survival compared with individuals with normal fat distribution regardless of BMI category. Caution Information on body fat distribution was based on anthropometric indicators alone. Implication Normal weight with central obesity may represent an important group for targeted lifestyle modifications and other preventive strategies. Obesity defined by body mass index (BMI) or measures of central obesity, such as waist-to-hip ratio (WHR) and waist circumference, is associated with increased total and cardiovascular mortality (13). However, a recent meta-analysis (4) showed that being overweight according to BMI was actually associated with lower total mortality, challenging the paradigm that BMI is linked to increased mortality. Further, whether measures of fat distribution provide any incremental risk information beyond BMI alone has been a major source of controversy (2, 3, 58). Indeed, the 2013 American Heart Association/American College of Cardiology/The Obesity Society guideline for the management of obesity (9) does not recommend measuring WHR and assumes that persons with normal BMI are not exposed to any obesity-related cardiovascular risk in view of the limited available data proving otherwise. A recent large study (6) showed that incorporating waist circumference information in prediction models did not increase the prognostic value already provided by BMI; however, for a given BMI category, subgroups of waist circumference or WHR were also associated with increased mortality risk. Other studies showed that measures of central obesity, such as WHR, waist-to-height ratio (10, 11), or waist circumference alone, may provide additional information beyond BMI on mortality risk among middle-aged adults, provided there is no adjustment for obesity-related cardiovascular risk factors (2, 3, 7). Further, a study (12) has shown that measures of central obesity are more strongly associated with total and cardiovascular disease mortality rates than BMI. Another study (13) showed that persons with normal body weight measured by BMI, but who had increased body fat measured by bioimpedance, have higher total and cardiovascular mortality rates and a higher prevalence of metabolic syndrome and its components than those with normal BMI and body fat content. In addition, a recent meta-analysis of individual-patient data in those with coronary artery disease (12) has shown that persons with normal BMI who are in the top tertile of central obesity measures had the highest total mortality rate. These results have been attributed to several factors. First, the diagnostic accuracy of BMI for obesity is not optimal, especially in persons with greater body fat percentages and normal or intermediate BMI (14). Second, those with normal body weight and higher body fat have less muscle mass, which is a factor associated with higher mortality risk and metabolic dysregulation (15, 16). Third, animal and human studies (17) have recently shown that adipose tissue in the legs and buttocks may have a favorable effect on glucose metabolism. Finally, persons with a central distribution of fat, particularly when measured with WHR, have less adipose tissue in the lower extremities (17). To our knowledge, no studies in the general U.S. population have specifically focused on assessing the mortality risk in persons with normal BMI and central obesity compared with those who are overweight or obese according to BMI. Thus, we hypothesized that persons with normal BMI and central obesity would have greater mortality risk than those who have any other combination of BMI and central obesity. We investigated the total and cardiovascular mortality risks associated with different patterns of body adiposity in a large cohort of participants in NHANES III (Third National Health and Nutrition Examination Survey) (1988 to 1994). Because hip circumference was not measured in the most recent National Health and Nutrition Examination Surveys (conducted yearly from 1999 to 2010) and WHR data to define central obesity were crucial to our primary hypothesis, we have used data from NHANES III instead. Methods Study Design and Participants NHANES III is a cross-sectional survey that produces generalizable health estimates for the U.S. population using a stratified, multistage, probability sampling design. From a sample of 39695 persons, 33994 were interviewed and 30818 were examined at mobile examination centers. The examination consisted of extensive anthropometric, physiologic, and laboratory testing. Waist and hip circumferences were measured by a trained examiner with a measuring tape positioned at the high point of the iliac crest for the waist and at the greatest circumference of the buttocks. The design and methods for the survey are available elsewhere (18). In our study, 16124 adults aged 18 years or older had WHRs available. Because extremely thin persons and those with a history of nonskin cancer have a higher mortality risk, we further restricted our analysis to persons with a BMI greater than 18.5 kg/m2 and those without a history of nonskin cancer. The resulting sample was 15184 participants (7249 men and 7935 women). Total and Cardiovascular Mortality Assessment Identifier data were matched to the National Death Index to determine mortality status, with mortality follow-up from the date of the NHANES survey through 31 December 2006. A complete description of the methodology to link baseline NHANES III data to the National Death Index can be found elsewhere (19). International Classification of Diseases, Ninth Revision (ICD-9), codes from 1986 to 1998 and International Classification of Diseases, 10th Revision (ICD-10), codes from 1999 to 2000 were used to ascertain the underlying cause of death. Cardiovascular deaths were defined as those with ICD-9 codes 390 to 398, 402, and 404 to 429 and ICD-10 codes I00 to I09, I11, I13, and I20 to I51 (NHANES III codes 53 to 75). Statistical Analysis The overarching analytic goal was to estimate the influence of various magnitudes of central obesity and BMI on total mortality. To do this, we conducted weighted survival modeling that enabled the estimation of the relative risk for mortality, quantified by the hazard ratio (HR), and the expected survival for NHANES III participants. The NHANES III survey design and sampling weights were incorporated into the statistical analysis to calculate weighted means, SEs for continuous variables, and weighted percentages for categorical variables. To determine the total mortality associated with the different patterns of adiposity, we created multivariable Cox proportional hazards models and adjusted for potential confounders previously shown to be associated with obesity and mortality (4). These variables were age at examination, sex, education level, and smoking history. Although we considered adjusting for obesity-related cardiovascular risk factors in the models, we did not adjust our final estimates for these factors. Epidemiologic obesity research has shown that it might be inappropriate to control for factors in the causal pathway between obesity and death, such as diabetes, atherogenic dyslipidemia, and hypertension. In testing for differences in mortality risk for combinations of central obesity (defined by WHR) and BMI, we considered higher-order interactions of WHR with BMI and other covariates. The association pattern of WHR and BMI was found to be different for men versus women (that is, statistically significant higher-order interaction terms), so the final modeling was conducted using sex-stratified data to more clearly present the findings. The interaction terms allowed the potential quadratic risks (U-shaped risks) of values for these variables. The estimated model contains polynomial functions of BMI and WHR (for example, BMI2 and BMI2WHR2). These terms allow for relationships that are more sensitive to change in risk for mortality based on unique combinations (profiles) of WHR and BMI. The estimated risk function, when other covariates in the model are controlled for, will resemble a saddle with high- and low-risk areas. When possible, covariates were the grand mean centered to lessen the collinearity induced from quadratic effects. Likelihood ratio tests were used to determine whether these higher-order model terms could be removed. The proportional hazards assumption for all variables was assessed and satisfied for the final models. After these models were established, we estimated HRs with estimated model variables for different combinations of WHR and BMI stratified by sex. For these comparisons, we chose a BMI of 22 kg/m2 to represent persons with normal BMI, 27.5 kg/m2 to represent overweight persons, and 33 kg/m2 to represent obese persons. For WHR, we chose 0.89 and 1.00 for men and 0.80 and 0.92 for women as a measure of central obesity. Each of these sets of values were chosen either to reflect the approximate midpoint of standard clinical interpretationsto avoid issues with values at common thresholds (for example, BMI values at 30 kg/m2)or to be clinical targets we sought to better understand. Wald-based (or large sample-based) HR estimates and their SEs were assessed to provide significance tests among these representative patient profiles (20). Once the fitted Cox model was deemed satisfactory, we sought to estimate measures of absolute risk by means-adjusted 5- and 10-year survival estimates (21). In this analysis, we replicated observations to standardize (reweight) them and ensure balance across sex, age, WHR, and BMI categories. The expected survival was computed as a weighted estimate