e mily o’brien, emil fosbol, andrew peng, karen alexander, matthew roe, eric peterson
DESCRIPTION
The Obesity Paradox: T he Importance for Long-term Outcomes in Non-ST-Elevation Myocardial Infarction – The CRUSADE Experience. E mily O’Brien, Emil Fosbol, Andrew Peng, Karen Alexander, Matthew Roe, Eric Peterson. Disclosures. None. Obesity in the United States. - PowerPoint PPT PresentationTRANSCRIPT
Emily O’Brien, Emil Fosbol, Andrew Peng, Karen Alexander, Matthew Roe, Eric Peterson
The Obesity Paradox: The Importance for Long-term Outcomes in Non-ST-Elevation Myocardial Infarction – The CRUSADE Experience
Disclosures
None
Obesity in the United States
CDC. Behavioral Risk Factor Surveillance System: 2010 survey data. Atlanta, GA: US Department of Health and Human Services, CDC; 2011.
0.5
BMI and Incident MIIn Individuals without Prior
MI
RR
(95%
CI)
18.5-24.9
<18.5 25.0-29.9
>=30
BMI
Eur Heart J. 2013 ;34(5):345-53.
21-23.5
BMI and Mortality Among STEMI Patients
18.5-21
<18.5
HR
(95%
CI)
4.0
1.0
0.25
BMI
26.5-28
23.5-25
25-26.5
28-30.0
>30.0
Int Jour of Obes. 2002; 26, 1046-1053.
The Paradox
2.0
The Obesity Paradox
First used to describe counterintuitive survival advantages in 19991
Reported for diabetes2, heart failure3, chronic kidney disease4, and CAD5
What is still unclear: Whether the paradox exists among older,
NSTEMI patients Persistence of effects over long periods of
followup Differential mortality associations by metabolic
status1Kidney Int. 1999;55(4):1560-1567.2JAMA. 2012;308(6):581-590.3Am J Cardiol. 2003;91(7):891-8944Am J Clin Nutr. 2005;81(3):543-5545Am J Med. Oct 2007;120(10):863-870
Objectives
To determine the association between body mass index (BMI) and risk of all-cause mortality over three years in a population of elderly NSTEMI patients
To determine whether BMI associations differ by “metabolically healthy” status
Methods
Data Sources CRUSADE linked to CMS data (2001-2006) National NSTEMI Quality Improvement Initiative Exclusions
»Patients transferred out (N=4474)»Patients missing information on height and/or weight
(N=2300)»Non-index admissions for patients with multiple
records (N=1329)»Died during hospitalization (N=2623)
Final Sample: N=34,465
Body Mass Index (BMI)
Calculated from weight and height on admission
WHO categories(kg/m2)6
<18.5 Underweight 18.5-24.9 Normal Weight 25-29.9 Overweight 30-34.9 Obese class I 35-39.9 Obese class II >=40 Obese class III
6World Health Organ Tech Rep Ser. 2000;894:i-xii, 1-253.
Objective II
Metabolically Unhealthy7
• Two or more of the following: 1. High blood pressure (>130/85 mmHG) or
hypertension2. Diabetes mellitus 3. High triglycerides (>150 mg/dl)4. Low HDL (<40 mg/DL in men, <50 mg/DL in women)
Metabolically healthy or “benign” obese• Preserved insulin sensitivity• Lower visceral fat accumulation
7Eur Heart J. 2013;34(5):389-397
Statistical Analysis Cox proportional hazards modeling with
censoring on death All-cause mortality over 3-years CRUSADE long-term mortality model8
AgeGender RaceFamily Hx of CADSmoking status
Prior MIPrior CABGPrior PCIPrior CHFPrior strokeHeart rate
HF at presentationECG findingsInitial HCT Initial troponin
8Am Heart J. 2011;162(5):875-883.
28%Obese
Obesity in CRUSADE
4%
32%
36%
18%
6%
4%
UnderweightNormal WeightOverweightObese Class IObese Class IIObese Class III
Patient Characteristics (%)
Obesity Class*
UnderWeight
(N=1236)
NormalWeight
(N=11186)
Over-Weight
(N=12506)
Obese I(N=6089)
Obese II(N=2226)
Obese III(N=1222)
Demographics Age in years (median) 82.0 80.0 77.0 75.0 73.0 72.0
Male Sex 30.7 49.3 59.4 54.7 46.1 35.5White Race 83.8 86.7 86.7 86.5 86.3 84.4
Medical history Hypertension 71.1 73.5 76.2 81.2 84.6 86.2
Diabetes 16.9 25.4 34.3 44.8 55.7 61.1Dyslipidemia 33.9 46.5 54.6 59.3 60.7 58.9
Current/Recent Smoker 19.7 14.3 12.5 10.6 10.1 9.9All-Cause Mortality
Unadjusted 3-year Mortality 62.4 45.6 31.8 28.0 29.5 32.8
Cumulative Incidence - Mortality
ResultsAll-Cause Mortality
Metabolically Unhealthy
Overall <18.5 18.5-24.9 25-29.9 30-34.9 35-35.9 >=400
102030405060708090
100
71.2%
47.8%
61.7%71.9%
81.2%85.7% 85.5%
% Metabolically Unhealthy
%
BMI Category (kg/m2)
Sensitivity AnalysisAll-Cause Mortality Metabolically Healthy Patients
Sensitivity Analysis
All-Cause Mortality Metabolically Unhealthy Patients
Potential Explanations
Selection bias: “healthiest” patients survive long enough to develop MI
Obese patients with more severe events may have greater metabolic reserve and increased resistance to catabolic burden
Cachexia abnormal cytokine & neurohormonal levels, mortality
BMI categories may have heterogeneous groups
Limitations
No followup after 3 years “Metabolically Healthy” classification
couldn’t be made in 1/3 of patients because HDL & triglycerides were not measured
No information on cause of death, which may be important to obesity paradox
Conclusions & Future Directions
The obesity paradox persists over the long term for NSTEMI
Similar associations between BMI and all-cause mortality for metabolically healthy patients
Further studies on metabolism and BMI are needed
Thank You!