High fiber low glycemic load diets in glucose homeostasis and body weight maintenance

1
High fiber/ low glycemic load diets in glucose
homeostasis and body weight maintenance

• Simin Liu, MD, ScD, MPH
• Professor of Epidemiology and Medicine
• Director, Program on Genomics and Nutrition,
• University of California, Los Angeles (UCLA)
• http//nutrigen.ph.ucla.edu
• CSCN-CSNS Annual Scientific Meeting,
• Toronto, May 29, 2008

2
Overview

• Background
• Obesity, diabetes, metabolic syndrome vs. insulin
  resistance epidemiology
• A diet that affects glucose homeostasis may be
  fundamental to vascular health and disease
• Dietary fibre, Glycemic index and glycemic load
  as functional measures to study diet and disease
  in human populations (e.g. diabetes and
  cardiovascular disease)
• Body weight and age as important modifiers for
  the effects of diet on risk of vascular diseases
• Perspectives

3
Obesity
4
                                             
                                                  
                                                  
                             Cumulative
lifetime risk for diagnosis of diabetes in the
US (Venkat Narayan et al, JAMA 2003)
5
Numbers of people with diabetes (in millions) for
2000 and 2010 (top and middle values) and the
percentage increase. Zimmet et al. Nature 2001
6
Epidemiology common risk factors for three
major chronic diseases
Risk factors Type 2 DM CHD
Colon Ca.
Age ???
??? ??? Tobacco ?
?? ?? Physical
inactivity ??
?? ?? Obesity ??????
?? ?? Excess energy intake
?? ??
?? Saturated fat ? ?
? ?? Red
meat ??
?? ? Refined carbohydrates
??? ??? ???
Dietary fibers ???
?? ?? Fruits
vegetables ??? ??
?? Whole grains
?? ??
?? Nuts/legumes ???
?? ?? Moderate Alcohol
?? ?? ??
7
Pathogenesis of DM/CHD Related to Insulin
Resistance
Diets (high GL/insulin demand)
Genes
Obesity
Insulin resistance
?Gluco-recognition ? Beta-cell mass ?Amyloid
deposit
Hyperinsulinemia
Hyperglycemia
Relative insulin deficiency
? Glycation of LDL ? Sorbitol ? NO/vasodilatory
response
Coronary Heart Disease
Liu, 1998 Liu and Manson, 2001
8
Dose-response relation between blood glucose and
CHD risk (Levitan et al. Arch Int Med, 2004)
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A New Diet-Heart HypothesisIf prolonged
hyperglycemia and hyperinsulinemia are parts of
the pathophysiologic pathways,as proposed by the
prevailing hyperglycemia-pancreatic exhaustion
hypothesis, then the physiologic impact of
different foods on serum glucose and insulin is
of critical importance and must be carefully
determined and quantified...Liu and Willett,
2001
10
Nutritional considerations relating to
carbohydrate classification and measurement -
Englyst Liu EJCN 2007
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Glycemic Index

• Different carbohydrates differ in their abilities
  to induce plasma glucose insulin responses.
• Glycemic index is a ranking of foods based on
  their glucose-raising potentials relative to that
  of white bread or glucose with the same amount of
  carbohydrate.

Jenkins et al. AJCN 1981
12
Glycemic Load (GL)

• GL ? GIi x CHOi x FPDi where
• GIi glycemic index for food i
• CHOi grams of carbohydrate per serving of food
  i
• FPDi frequency of servings of food i per day
  during the past year.
• Each unit of glycemic load represents the
  glycemic equivalent of one gram of carbohydrate
  from white bread

13
Conceptual Framework Evaluating the Consistency
of Evidence
Dietary Pattern
low GI/GL
Foods
Whole grains/plants
Metabolic Disorders
Nutrients
fiber, Mg2 etc.
Bio-markers glucose, lipids, cytokines and
hormones etc.
Genetic variants
VDR, AR, ER, SHBG etc.
Adapted from Liu and Manson, Curr Opin Lipidol,
2001
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Glycemic Load and IndexEstimated change in human
diet over time
Industrial revolution
E CHO
Agricultural revolution
Ice Ages
100,000
10,000
1000
100
Present
1,000,000
Years ago
1) glycemic load, 2) fatty acid composition, 3)
macronutrient composition, 4) micronutrient
density, 5) acid-base balance, 6)
sodium-potassium ratio, and 7) fiber content.
Hirsch. Am J Clin Nutr 1995Cordain et al, 2005
15
Increasing prevalence of Type 2 DM in the US with
increasing Consumption of Carbohydrates
Increasing prevalence of type 2 DM in the US
with increasing consumption of refined
carbohydrates

National Nutrient Databank
Centers for Disease Control and Prevention

Gross et al AJCN 2004
16
Relative Risk of Type 2 Diabetes by Cereal Fiber
and Glycemic Load
WOMEN
Relative Risk
lt2.5 g/day
(ref)
2.5 -5.8 g/day
Cereal Fiber
gt5.8 g/day
gt165
165-143
lt143
Glycemic Load
(Salmeron et al,1997)
9.038
17
Multivariate relative risk of CHD by body mass
index and glycemic load
Liu et al 2000
18
Glycemic index or load and metabolic
intermediates

• ? GI/GL --gt ? LDL, C peptide, HbA1c, fasting TG
  or hsCRP in both diabetic and healthy subjects
  (Jenkins et al 1987 1992 Wolever et al 1992,
  Brand-Miller 1994 Liu et al 2001 Liu et al
  2002 Pereira et al 2004 Ebbeling et al 2005)
• ?GI/GL --gt improved insulin sensitivity among
  patients with CHD or overweight participants
  (Frost et al, 1996 1998 McKeown et al 2004
  Pereira et al, 2004)
• ?GI/GL --gt increased plasma levels of cytokines
  (Richter et al, 2004, Lu et al. 2005, Levitan et
  al, 2007, Ma et al, 2008)

19
Fasting plasma TG concentrations by GL, GI and
carbohydrate intake
Nurses Health Study
Fasting Triglycerides (mg/dl)
Liu et al. AJCN 2001
12.039b
20
Changes in fasting TG corresponding to changes in
energy from fat in metabolic experiments and
the NHS
21
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Relation between HDL-cholesterol concentration
and glycemic index in men and women (Frost et al,
1999)
23
Mean concentrations of HDL by glycemic index
among men and women aged 20 years, NHANES III,
1988-1994 (Ford and Liu, Arch Int Med 2000)
Women
Men
Plt0.0001
Adjusted for age, race or ethnicity, education,
smoking status, body mass index, alcohol intake,
physical activity, percent kilocalories from
protein (quintiles), percent kilocalories from
fat (quintiles), total energy intake (quintiles).
24
Dietary GL and clinical diabetes by status of
insulin resistance (Villegas R, Liu S et al.
Arch Int Med 2007)
Adjusted for age, kcal/day, smoking, alcohol,
education, income, occupation and
hypertension. High Risk BMIgt23 kg/m2 and
WHRgt0.85 and Low Physical Activity Low Risk
Group all other participants
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(No Transcript)
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Mean BMI at each time period by Intake of whole
grains
B M I
Year
Liu et al. AJCN 2003
27
12-year weight change attributed to grain intake
in the NHS, 1984-1996
Adjusted for age, follow-up interval, exercise,
smoking, alcohol, caffeine, use of HRT, total
caloric intake, and baseline BMI.
Liu et al. AJCN 2003
28
Pooled relative risk of type 2 diabetes
associated with whole grain / high fiber diet
RR ( confidence interval) 0.73 (0.55,
0.97) 0.72 (0.58, 0.90) 0.78 (0.64,
0.96) 0.62 (0.54, 0.72)
Salmeron et al. Salmeron et al. Meyer et al.
Liu et al. Fung et al. Stevens et al. Montonen et
al. Liu et al.


0.70 (0.57, 0.85) 0.75 (0.61,
0.93) 0.65 (0.36, 1.18) 0.86 (0.69,
1.08) 0.71 (0.66, 0.77)




Combined
.5
1
1.5
Relative Risk

• Horizontal lines confidence intervals
• Size of the Squares the weights of the
  individual studies to the final summary relative
  risks
• Dotted line final summary relative risk
• Risk reduction observed in the group with highest
  intake of whole grain/ high fiber compared with
  the group with lowest intake
• data from Womens Health Study Liu AJCN 2002
  Liu et al. AJCN 2003

29
Relative Risk
Liu et al. JACC 2002
30
Inflammatory markers predictive of clinical
diabetes risk among women participated in the
Womens Health Initiative, 1998-2004 Liu et al
Arch Int Med 2007
31
Liu et al. AJCN 2002
32
Figure 1. Geometric means and 95 confidence
interval of high sensitivity serum C-reactive
protein (hs-CRP), interleukin 6 (IL-6), and tumor
necrosis factor a (TNF-a) by quartile of dietary
total fiber, soluble, or insoluble fiber from
multivariable linear regression analyses
(N1958), Women's Health Initiative (WHI)
Ma Y, Hébert JR, Li W, Bertone-Johnson ER, Ockene
IS, Olendzki BC, Pagoto SL, Rosal MC, Ockene JK,
Tinker L, Griffith JA, and Liu S. Association
between dietary fiber and inflammatory markers in
an ethnically diverse cohort of postmenopausal
women. Nutrition, in press.
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Conclusion (1)

• A dietary pattern characterized by high GI can
  adversely affect metabolic intermediates and may
  increase risk of DM and CHD, especially among
  those who are prone to insulin resistance

34
Conclusion (2)

• Due to our genetic mal-adaptation to our
  westernized lifestyles/environments, we are
  becoming a metabolically efficient people
• This can be easily characterized by very simple
  measures of glucose homeostasis or BMI
• When thinking about diet, which is only one
  aspect of our westernized environment, we need to
  keep in mind what kind of people we have become
  metabolically
• Consider body weight and age as modifiers when
  assessing diet-disease relation
• Need to replace refined grains with whole grain
  products to improve glucose homeostasis and
  vascular health

35
Future research

• Characterize plant-based nutrients and
  phytochemicals
• Measure glycemic effect of whole-grain products.
• Refine and standardize food composition database
• Examine interactions-not only among different
  dietary factors, but also between diet and
  genetic predisposition and between diet and
  metabolic determinants such as physical activity
• Conduct large randomized trials focusing on
  plant-based foods or promising components (e.g.,
  mg)?
• Surveillance
• Liu, S Arch Int Medicine 2006

36
Acknowledgements -

• Students and Fellows
• Brian Chen
• Sara Chacko
• Jodie Katon
• Rachelle Rohwer
• Gina Wallar
• Tin-Lun Tang
• Yuko You
• Lingling Fu
• Rebecca Chao
• Eric Ding
• Research Faculty and Staff
• Angela Presson
• Sean Hsu
• Yiqing Song
• Tianhua Niu
• James Sul
• Lin Wang
• Chris Roberts

• Collaborators
• Jake Lusis
• Lauren Nathan
• Steve Horvath
• Leo Morales
• Thomas Drake
• Zuo-Feng Zhang
• Jacques Rossouw, NHLBI
• Lesley Tinkers, Fred Hut
• Lew Kuller, WHI
• Barbara Howard, WHI
• Earl Ford, CDC,
• JoAnn Manson, BWH
• Julie Buring, BWH
• Frank Hu, HSPH
• Nadir Rafai, Children Hospital, Boston
• Jun Liu, Harvard
• Walter Willett, HSPH
• Participants in Nurses Health Study, Womens
  Health Study, Physicians Health Study, Shanghai
  Womens Health Study, Womens Health Initiative,
  NHANES,/CDC and our smal clinical trials

http//nutrigen.ph.ucla.edu