Dr Arun Chawla discusses Obe

1. Reverse Epidemiology of
Obesity in Kidney Disease
Arun Chawla, MD
Hofstra NSLIJ School of Medicine

5. Overview
 Conventional epidemiology
 Paradox
 Studies…
 Hypothesis to explain what we see
 Paradox within paradox

6. What we all know… for Now!
 In US, obesity is the second leading cause of
preventable disease and death.
 Associated with ESRD - type 2 DM and
hypertension.
 Epidemic growing and life expectancy being
shortened.

7. Prevalence of overweight, obesity and extreme obesity among
adults: United States, trends 1976-80 through 2005-2006
NHANES December 2008

8. Associated co morbidities
 Type 2 DM  ESRD
 Hypertension  NASH
 CAD  VTE
 GDM  Cholelithiasis
 OSA  Depression
 Hyperlipidemia  Pulmonary Hypertension
 OA  CTS
 GERD  Infertility
 Gout  Breast/Colon cancer

9. Multivariate Relative Risk of Death from CVD, Cancer, and All Other Causes
among Men and Women Who Had Never Smoked and Who Had No History of
Disease at Enrollment, According to BMI
Calle E et al. Nejm 1999

10. Multivariate Relative Risk of Death from All Causes among Men and
Women According to BMI, Smoking, and Disease Status
Calle E et al. N Engl J Med 1999

11. So…
 Given the magnitude of the risks of obesity in
the general population, it is important to clarify
whether these risks apply to patients on dialysis,
who have an overall cardiovascular risk at least
10 times greater than the general population.

12. First thoughts….
 In 1982, Degoulet et al looked into 1453
subjects treated in 33 French dialysis centers
over 5 years and noticed no increase in mortality
with higher BMI.
 After 17 years came the first trial …

13. Influence of Excess Weight on
Mortality and Hospital Stay in 1346
Dialysis Patients
Fleishmann and Salahudeen
Kidney International 1999

14. Methods
 Cohort of 1346 HD patients in Mississippi
 Followed prospectively for 1 year for
hospitalization and mortality.
 On dialysis for more than 90 days (avg. 4.3 yrs)
 38% had BMI >27.5
 13% had BMI <20
 Normal considered BMI of 20-27.5

15. Kaplan-Meier Death Hazard
Death Hazard
400
Survival in days
Fleishmann et al. Kidney International 1999

16. Results
 Causes of death similar amongst three groups.
 For a unit increase in BMI>27.5 risk of dying
showed RR reduction of 6% in the univariate
model and 4% in the multivariate model.
 With 1 unit decrease of BMI below 20 the risk
of death increased by 1.6 fold.

17. Hospital admission rate per year and
Length of stay (LOS)…
1.8 16
1.6 14
1.4 12
1.2
10
1
8
0.8
6 LOS
0.6
0.4 4
0.2 2
0 0
Underweight Overweight underweight Normal Overweight
Ad Rate weight

18. Conclusion
 Special attention to nutrition to achieve high end
of normal BMI may help to reduce morbidity
and mortality in hemodialysis patients.
 Results were significant even after adjustment
for markers of nutrition like albumin, transferrin
and creatinine.

19. Limitations
 Smaller sample size
 Mainly AA (88%) so no diversity
 Survival advantage not shown in Caucasians
 Short follow up
 BMI not the most accurate tool to comment on
body composition.

20. Questions
 Fat mass or muscle mass?
 Mild versus severe obesity?
 Is high BMI only a short term advantage?
 Interactions of race or ethnicity?

21. Association of Body Size with Outcomes
Among Patients Beginning Dialysis
Johansen Et al
Am J Clinical Nutrition 2004

22. Hypothesis
 Extremely high BMI would not be associated
with increased survival time.
 If there were a survival advantage at higher BMI,
it would be explained in part by the increased
lean body mass (LBM) that usually accompanies
high BMI.

23. Methods
 Data obtained from the USRDS and CMS.
 Mortality, hospitalisation and dialysis modality
(i.e. HD or PD), for adult patients beginning
dialysis between April 1, 1995, and November
30, 2000.
 Follow-up extended through November 30,
2001 with median follow up of 2 years.

24. FIGURE 1. Hazard ratios for death among men ({blacksquare}) and women ({square}) by
category of BMI (A), Benn index (B), and estimated fat mass (C)
Death Hazard
Johansen, K. L et al. Am J Clin Nutr
Copyright ©2004 The American Society for Nutrition BMI 2004

25. Effects of adjustment for serum creatinine and creatinine
index on the relation between BMI and survival
Curve more steep!!!
Death Hazard
BMI
Copyright ©2004 The American Society for Nutrition Johansen, K. L et al. Am J Clin Nutr 2004

26. Conclusions
 BOTH THEIR HYPOTHESIS PROVED WRONG!!!
 Higher adiposity was associated with increased
survival, even after adjustment for demographics,
laboratory values, comorbidities, dialysis modality and
even when adiposity was assessed by different methods.
 Pattern observed even for cardiovascular death
 Less evident with PD and Asians

27. Strengths
 Large sample size
 Complete data
 All racial and ethnic groups
 Longer follow up
Limitations
 Observational design

28. Does weight gain help????
Association of Morbid Obesity and Weight
Change Over Time with Cardiovascular
Survival in Hemodialysis Population
K.Kalantar-Zadeh et al
Am J Kidney Diseases 2005

29. Methods
 Patients enrolled with DA Vita Inc
 Cohort on July 1, 2001 and subsequently
patients were enrolled through June 30, 2003-
Non-concurrent cohort.
 Data organized to form “8 quarterly mean
values” to include 2 year observation period.
 11 categories <18, >45 and then 9 in between
18 and 44.9

30. Data collected
 CBC, BUN, Hemoglobin, albumin, creatinine (muscle
mass), dialysis dose and ferritin and TIBC (marker of
nutrition).
 For each analysis, 3 models were examined based on
the level of multivariate adjustment:
(1) the unadjusted model
(2) case-mix– adjusted models
(3) case-mix and laboratory

31. 39.3
15.9
K.Kalantar-Zadeh et al Am J Kidney Dis 2005

32. Fig 1. Time-dependent association between BMI and 2-year
all-cause mortality in 54,535 MHD patients
K.Kalantar-Zadeh et al Am J Kidney Dis 2005

33. Fig 2. Time-dependent association between BMI and 2-year
cardiovascular mortality in 54,535 MHD patients
K.Kalantar-Zadeh et al Am J Kidney Dis 2005

34. Fig 4. Association between the rate of weight change over
time and subsequent all-cause mortality in 46,629 HD patients
p.068
P<.0001
K.Kalantar-Zadeh et al Am J Kidney Dis 2005

35. Fig 5. Association between the rate of weight change over
time and cardiovascular mortality in 46,629 HD patients
P .101
P<.001
K.Kalantar-Zadeh et al Am J Kidney Dis 2005

36. Conclusions
 Even after exhaustive adjustment for time varying laboratory
markers, both all-cause and cardiovascular mortality showed
decreasing rates across increasing BMI categories, even morbid
obesity.
 Lower BMI at baseline consistently is found to be a strong
predictor of elevated mortality.
 Weight loss was associated with increased CV and all-cause
death, whereas weight gain showed a trend toward improved
survival and reduced cardiovascular mortality.

37. Association Of Low Body Mass Index And Weight
Loss With Increased Mortality In 14,065 Transplant-
wait-listed Hemodialysis Patients
K.Kalantar-Zadeh et al Circulation 2008

38. What we Now know…!
Leavey SF, et al. Body mass index and mortality in ‘healthier’ as compared with' sicker’ hemodialysis patients:
results from the Dialysis Outcomes and Practice Patterns Study (DOPPS). Nephrology Dial Transplant 2001

39. ?????

40. Hypothesis

41. TNF- alpha receptors in obesity
 TNF-alpha is elevated in CHF and in dialysis
patients and may contribute to cardiac injury
through its pro-apoptotic and negative inotropic
effects (2).
 Adipose tissue produces soluble TNF-alpha
receptors, which may play a cardio-protective
role.
2) Feldman et al. The role of tumor necrosis factor in the pathophysiology of
heart failure. J Am Coll Cardiol 2000; 35:537– 44.

42. Neurohormonal alterations
 The lean subjects had significantly higher increases in
plasma adrenaline and renin concentrations during
treadmill testing, despite similar baseline values and a
history of hypertension (3).
 Heightened sympathetic and renin-angiotensin activities
are associated with a poor prognosis in heart failure and
fluid overload states (such as those seen in dialysis
patients).
3) Weber MA et al. Contrasting clinical properties and exercise responses
in obese and lean hypertensive patients. J Am Coll Cardiol 2001;37:169 –74

43. Selection Bias

44. More stable hemodynamic status
 Despite having similar PCWP and cardiac
indexes, overweight and obese patients with
fluid overload tend to have higher systemic
blood pressure values (1).
 Due to better tolerance larger proportion of
obese and overweight patients take ACE
inhibitors.
1) Horwich et al . The relationship between obesity and mortality in patients
with heartfailure. J Am Coll Cardiol 2001;38:789 –9

45. Endotoxin-lipoprotein hypothesis
 Lower serum total cholesterol and lipoprotein
concentrations are strongly and independently
associated with impaired survival in dialysis (4).
 It reflects a richer pool of internal lipoproteins that can
actively bind to and remove circulating endotoxins,
which effectively retards inflammation and subsequent
atherosclerosis (5).
4) Nishizawa et al. Paradox of risk factors for cardiovascular mortality in uremia: is a higher cholesterol level
better for atherosclerosis in uremia? Am J Kidney Dis 2001;38 S4–7.
5) Niebauer J, et al. Endotoxin and immune activation in chronic heart failure: a prospective cohort study.
Lancet 1999;353: 1838–42.

46. Malnutrition-inflammation complex
syndrome – “Cachexia in slow
motion”
 Undernourished people more likely to develop PEM and slow to
recover form illnesses and its complications.
 Increased release of IL-6 and TNF may suppress appetite (6),
may cause muscle proteolysis and hypoalbuminemia, and may be
involved in the processes that lead to atherosclerosis.
 Patients with lower albumin, low cholesterol, creatinine and
homocysteine concentration might represent MICS making them
prone to infection and inflammation and slower recovery.
 Nutritional Inflammatory hypothesis
(6) Kalantar-Zadeh K. Appetite and inflammation, nutrition, anemia, and clinical outcome in hemodialysis
patients. Am J Clin Nutr 2004.

47. Time discrepancies among
competitive risk factors
 US population versus  Survival advantages that exist
developing countries in obese dialysis patients may,
in the short term, outweigh
the harmful effects of these
risk factors on CVD in the
long term.
 Dialysis patients, ironically,
do not live long enough to
die of the consequences of
overnutrition!

48. Dialysis modality????
Body mass index, Dialysis Modality, and
Survival: Analysis of the United States
Renal Data System Dialysis Morbidity and
Mortality Wave II Study
ABBOTT et al
KIDNEY INT. 2004

49. Methods
 Retrospective cohort study of the USRDS
DMMS Wave II database.
 Patients who started dialysis in 1996 and were
followed until October 2001 (5yrs)
 Outcome: Mortality
 Divided into 4 groups 1 (<21.9), 2 (21.9-24.9),
3 (25-29.9) and 4(>29.9)

50. Demographic and clinical variables
 PD patients-
Less AA, younger, more renal transplant.
Decreased prevalence of CAD, CHF, CVA, LVH on
EKG, PVD, and cancer.
Decreased Erythropoietin use
Higher ACE, statins and beta blockers.
 No significant difference of BMI

51. PD patients
In the lowest group were at an increased risk of mortality

52. Kaplan-Meier plot of patient survival by BMI
HD survival 39.8% vs. 32.3% PD survival 38.7% vs. 40.4%
ABBOTT et al KIDNEY INT. 65

53. Conclusions
 Low BMI was independently associated with
higher mortality regardless of dialysis modality.
 HR for death in patients with BMI >30 was 0.89
for HD and significant while no such correlation
in PD patients.

54. “Paradox within paradox”
 Adequacy of dialysis not known.
 Whether “uremic” and “inflammatory” malnutrition
differ by dialysis modality has not been established.
 Changes in B.P, med use, lab values etc. wasn’t
followed.
 1.5–4.25% of dextrose in their peritoneal dialysate
(often around the clock), which is estimated to be
absorbed at 45%.

55. CKD patients??
(1)Evans et al; Natural history of chronic reanl failure; Results from an unselected population cohort in
(2)BMI and mortality in CKD. Madero et al Abstract JASN 2006
(3)Reverse epidemiology in patients with CKD. Kovesdy etal. Seminars in Dialysis 2007