Paradoja de la Obesidad

“Paradoja de la Obesidad” Francisco J. Pasquel, MD Assistant Professor of Medicine Emory University School of Medicine Director, Endocrine Clinic Gr...
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“Paradoja de la Obesidad”

Francisco J. Pasquel, MD Assistant Professor of Medicine Emory University School of Medicine

Director, Endocrine Clinic Grady Health System

Definición • La obesidad se asocia con una menor mortalidad

en individuos con enfermedades crónica • Este asociación, inversa-contraintuitiva, la "

paradoja de la obesidad ”, se ha asociado con: – Enfermedades cardiovasculares

– Diabetes – Fractura de cadera Lajous et al. The American Journal of Medicine, Vol 128, No 4, April 2015

Asociación de IMC y complicaciones en pacientes hospitalizados con diabetes

IMC entre 22 y 40+ Menor riesgo de complicaciones?

Unpublished data

Asociación de IMC y complicaciones en pacientes hospitalizados con glucosa normal

IMC entre 25 y 40+ Menor riesgo de complicaciones?

Unpublished data

Artefacto? •

Del latin: arte factus: –hecho con arte

Risk-Adjusted Survival Curves for the 4 Body Mass Index Categories at 5 Years in a Study of 1,203 Individuals With Moderate to Severe Heart Failure

Hprwich et al. J Am Coll Cardiol 2001;38:789 –95

The American Journal of Medicine, Vol 128, No 4, April 2015

J Am Med Dir Assoc 2008; 9: 302–312

CAD and CHF

Hainer et al, Diabetes Care, Vol 36, 2013

Other manifestations of obesity paradox •

Peripheral arterial disease



Stroke



Thromboembolism



Post-procedure complications (cardiac surgery, ablation Afib)



SICU mortality



Mortality non-bariatric surgery



Type 2 Diabetes



Amputation Risk



COPD



Hemodialysis patients



Critically Ill



Osteoporosis

Hainer et al, Diabetes Care, Vol 36, 2013

Body Fat and IMC and Survival

Kaplan-Meier Survival Estimates Comparing Mortality in Participants Stratified by Weight Status at the Time of Incident Diabetes (A: TOTAL Mortality)

Carnethon et al, JAMA. 2012;308(6):581-590

Kaplan-Meier Survival Estimates Comparing Mortality in Participants Stratified by Weight Status at the Time of Incident Diabetes (CV Mortality)

Carnethon et al, JAMA. 2012;308(6):581-590

Kaplan-Meier Survival Estimates Comparing Mortality in Participants Stratified by Weight Status at the Time of Incident Diabetes (NON-CV Mortality)

Carnethon et al, JAMA. 2012;308(6):581-590

Clarck et al. Am J Cardiol 2012;110:77– 82

McAuley et al. Mayo Clin Proc. 2012;87(5):443-451

McAuley et al. Mayo Clin Proc. 2012;87(5):443-451

Kaplan-Meier survival curves according to BMI (in kg/m2) or body-composition analysis in patients with cancer

A: Survival curves according to BMI groups. B: Survival curves according to a low FFMI or a normal or high FFMI. C: Survival curves according to FMI. D: Survival curves according to body-composition classification. FFMI, fat-free mass index; FMI, fat mass index.

Gonzalez et al, Am J Clin Nutr 2014;99:999–1005

5-Year Mortality in Patients With Coronary Artery Disease Based on Different Combinations of Body Mass Index With Central Obesity (Waist Circumference)

Coutinho et al, JACC Vol. 61, No. 5, 2013

Mortality Risk of Subjects With Normal Weight Central Obesity Compared With Subjects With Other Patterns of Adiposity, Using Waist Circumference as a Measure of Central Obesity

Coutinho et al, JACC Vol. 61, No. 5, 2013

From: The Obesity Paradox in Type 2 Diabetes Mellitus: Relationship of Body Mass Index to Prognosis: A Cohort Study Ann Intern Med. 2015;162(9):610-618. doi:10.7326/M14-1551

Unadjusted Kaplan–Meier estimates of cardiovascular events and all-cause mortality. Patients were followed for a median of 10.6 y (interquartile range, 7.8–13.4). Admissions for ACS occurred in 912 patients (9%), CVA in 760 patients (7%), and HF in 598 patients (6%); 3728 patients (35%) died. ACS = acute coronary syndrome; BMI = body mass index; CVA = cerebrovascular accident; HF = heart failure.

Unadjusted Kaplan–Meier estimates of cardiovascular events and all-cause mortality

Ann Intern Med. 2015;162(9):610-618. doi:10.7326/M14-1551

Cox regression analysis, according to BMI categories, for cardiovascular events and all-cause mortality in patients with T2D

Figure Legend:

Ann Intern Med. 2015;162(9):610-618. doi:10.7326/M14-1551

Obesity and Heart Failure

Lavie et al. Heart Failure Clinics, Volume 10, Issue 2, 2014, 319–326

“paradoja de la obesidad” entre los fumadores obesos con disglucemia pero no entre los no-fumadores obesos con disglucemia?

“Al condicionar de acuerdo al estado de la enfermedad, el efecto de confusión de fumar es exagerado, causando que una exposición nociva, como la obesidad , aparezca como un efecto de protección”

Banack & Kaufman, Eur J Epidemiol (2015) 30:1111–1114

Algunos investigadores han sugerido que los análisis de la relación obesidad - mortalidad deben limitarse a los no-fumadores para eliminar por completo la fuerte confusión del fumar

de Gonzalez Berrington, NEJM 2010

Estimated Hazard Ratios for Death from Any Cause According to Body-Mass Index for All Study Participants and for Healthy Subjects Who Never Smoked

Berrington de Gonzalez et al N Engl J Med 2010;363:2211-9

Estimated Hazard Ratios for Death from Any Cause among Healthy Subjects Who Never Smoked, According to Body-Mass Index and Age at Baseline

Berrington de Gonzalez et al N Engl J Med 2010;363:2211-9

Estimated Hazard Ratios for Death from Specific Causes among Healthy Subjects Who Never Smoked, According to Body-Mass Index

Berrington de Gonzalez et al N Engl J Med 2010;363:2211-9

Un problema estadístico?

Relationship between Smoking and Obesity (UK General Population)

N= 499,504 Middle- Aged Adults

Dare et al. PLoS ONE 10(4): e0123579

Sesgos • Fumar es a menudo identificado como un

factor de confusión en la relación con la mortalidad asociada a obesidad • El sesgo de selección puede amplificar la magnitud de un sesgo de confusión existente • “Collider Bias” Eur J Epidemiol (2015) 30:1111–1114

Representación gráfica del sesgo

U : unmeasured confounders

Banack & Kaufman, Eur J Epidemiol (2015) 30:1111–1114

Qué podemos hacer al respecto?

Randomizar

FreeDigitalPhotos.net /Gualberto107/KEKO64

Tobias et al. N Engl J Med 2014;370:233-44.

Tobias et al. N Engl J Med 2014;370:233-44.

Hazard Ratios for All-Cause Mortality among Participants with Incident T2D, According to Body-Mass Index (BMI) Shortly before Diagnosis of T2D.

Tobias et al. N Engl J Med 2014;370:233-44.

Hazard Ratios for All-Cause Mortality among Participants with Incident T2D, According to Body-Mass Index (BMI) Shortly before Diagnosis of T2D.

Tobias et al. N Engl J Med 2014;370:233-44.

Hazard Ratios for All-Cause Mortality among Participants with Incident T2D, According to Body-Mass Index (BMI) Shortly before Diagnosis of T2D.

Tobias et al. N Engl J Med 2014;370:233-44.

Conclusion • Hay una relación en forma de J entre el IMC al momento del diagnóstico de diabetes y el

riesgo de muerte. El menor riesgo se observa entre los participantes de peso normal con un IMC de 22,5 a 24,9

Conclusion • En el estudio de Tobias et al, no hubo evidencia de un

efecto protector de sobrepeso u obesidad sobre la mortalidad • Además , dada la relación de sobrepeso y obesidad con otras enfermedades de interés público (ECV y el cáncer ) , el mantenimiento de un peso corporal saludable debe seguir siendo la piedra angular de manejo de la diabetes

Weight change over 3 years in MOVE! participants and eligible non-participants

Jackson et al. Lancet Diabetes Endocrinol 2015; 3: 173–80