Diet and Metabolic Syndrome:
Practical Approaches to Lowering
Risks of Heart Disease and Diabetes
Kevin C. Maki, PhD, FNLA, FTOS
Midwest Center for Metabolic &
Cardiovascular Research and
DePaul University
Chicago, Illinois
The Metabolic Syndrome
 A cluster of risk factors for heart disease and type
2 diabetes that occur together more than would
be predicted by chance
 Has been known by several names:
– Syndrome X
– Insulin Resistance Syndrome
– The Deadly Quartet
Metabolic Syndrome: Prevalence in
U.S. by Age – 2001 ATP III Defn.
Men
Women
40-49
50-59
Prevalence (%)
50
40
30
20
10
0
20-29
30-39
Age (years)
Ford, et al. JAMA. 2002;287:356-9.
60-69
70+
Metabolic Syndrome Definition
(AHA/NHLBI Revised)
 Any three of the following:
– Abdominal obesity: waist circumference
>102 cm (40 inches) for men
 > 88 cm (35 inches) for women

– Triglycerides: ≥150 mg/dL (or meds)
– HDL cholesterol (or meds)
< 40 mg/dL (men)
 < 50 mg/L (women)

– Blood pressure: ≥130/85 mmHg (or meds)
– Fasting glucose: ≥100 mg/dL (or meds)
Additional Features of the Metabolic
Syndrome (Under the Surface)
 Insulin resistance and hyperinsulinemia
 Small, dense LDL particles (Pattern B)
 Pro-thrombotic and inflammatory states
– ↑ fibrinogen
– ↑ plasminogen activator inhibitor-1
– ↑ C-reactive protein
 Elevated uric acid
 Hypertrophy or hyperplasia
– Heart, blood vessels, prostate, tumors
Diabetes Mellitus: a US Pandemic
• Diabetes mellitus affects 25.8 million people or 8.3% of
the US population (1/3 undiagnosed)
• It is estimated that 79 million US adults have prediabetes
• Type 2 diabetes mellitus (T2DM) is a major cause of
heart disease and stroke, and is the leading cause of
kidney failure, lower-limb amputations, and blindness
• Annual economic impact (direct and indirect): $174
billion
http://www.ndep.nih.gov/diabetes-facts/#howmany
Pathogenesis of Type 2 Diabetes:
the Traditional Triumvirate
HGP = hepatic glucose production
DeFronzo RA. Diabetes. 2009;58:773-795.
Glucose and Insulin Responses During 100 g
Oral Glucose Tolerance Test (OGTT)
180
Plasma Insulin (mU/L)
Plasma Glucose (mg/dL)
130
120
110
100
90
80
140
120
100
80
60
40
20
0
0
Normal
160
60
120
Time (min)
Insulin Resistance
0
Normal
Maki KC. Unpublished data.
60
120
Time (min)
Insulin Resistance
Matsuda Index * AUC ins/glu
Beta-Cell Function in NFG, IFG, and Diabetes
Oral disposition index
1400
1200
1000
All comparisons p < 0.001
800
600
400
200
0
NFG
IFG
Maki KC, et al. Nutr J. 2009;8:22.
Diabetes
Glucose and Insulin Responses During a
Liquid Meal Tolerance Test
300
200
150
100
NFG
IFG
Diabetes
140
Insulin (mU/L)
250
Glucose (mg/dL)
160
NFG
IFG
Diabetes
120
100
80
60
40
50
20
0
0
0
30 60 90 120 150 180 210 240
Time (min)
0
30
60
90 120 150 180 210 240
Time (min)
NFG = normal fasting glucose, IFG = impaired fasting glucose
Maki KC, et al. Nutr J. 2009;8:22.
Pathogenesis of Type 2 Diabetes:
Quartet of Essential Defects
DPP-IV = dipeptidyl peptidase-4
TZDs = thiazolidinediones
DeFronzo RA. Diabetes. 2009;58:773-795.
Role of Nocturnal Free Fatty Acids (FFAs) in DietInduced Obesity/Insulin Resistance in Dogs
Dashed lines
indicate 9:00 am
feeding
Open bars are
pre- and filled
bars are postdiet-induced
obesity
Kim SP, et al. Am J Physiol Endocr Metab. 2007;292:E1590-E1598.
Raising FFA Induces Insulin Resistance in
Healthy Subjects
FFA level (µmol/L)
• Saline n = 422
• Intralipid n = 588
LBM = lean body mass
Mathew M, et al. Cardiovascular Diabetology. 2010:9:9.
Lowering FFA with Acipimox Increases
Insulin Sensitivity
Cusi K, et al. Am J Physiol Endocrinol Metab. 2007;292:E1775-E1781.
Relation Between Weight Loss and Insulin
Sensitivity According to Dietary CHO
SSPG = steady-state
plasma glucose
McLaughlin T, et al. Am J Clin Nutr. 2006;84:813-821.
Defects in Dysglycemia: Muscle, Liver,
Pancreas, Adipose Tissue
• Insulin resistance
 Reduced ability of a given circulating level of insulin to enhance tissue
uptake of glucose (particularly in skeletal muscle)
 Reduced ability of a given circulating level of insulin to suppress hepatic
glucose output and release of FFA from adipose depots
• Excessive hepatic glucose output
 Hepatic insulin resistance
 Excess glucagon release + other factors (e.g., neural control)
• Pancreatic beta-cell dysfunction
 Reduced insulin response to a rise in plasma glucose

Reduced sensitivity to glucose signaling

Incretin resistance and deficiency

Lower insulin secretion capacity in advanced T2DM
Risk Factors for Diabetes







Pre-diabetes (IGT, IFG, elevated HbA1C)
Overweight/obesity
Physical inactivity
Age ≥45 y
Family history of diabetes
Metabolic syndrome and its components
Certain racial and ethnic groups (e.g., Non-Hispanic Blacks,
Hispanic/Latino Americans, Asian Americans, Pacific Islanders,
American Indians and Alaska natives)
 Women who have had gestational diabetes, or given birth to a baby
weighing ≥9 lbs
http://www.diabetes.org/diabetes-basics/prevention/risk-factors/
Pre-Diabetes
Test
Range of values
Fasting plasma glucose (FPG)
100-125 mg/dL
2-hr plasma glucose, 75 g OGTT
140-199 mg/dL
Glycated hemoglobin (HbA1C)
5.7-6.4%
ADA. Diabetes Care. 2010;33(Suppl 1):S62-S69.
Diabetes Prevention Studies Overview:
Hypoglycemic Agents
Study
Subjects
Total N
F/U (y)
Intervention Diabetes
Risk ↓
U.S. DPP
IGT
3234
2.8
0.9
Metformin
Troglitazone
31%
75%
India DPP
IGT
531
2.5
Metformin
Metformin +
diet/exercise
26%
28%
India DPP-2
IGT
407
3.0
Pioglitazone
NS
U.S. ACT NOW
IGT
602
2.4
Pioglitazone
72%
U.S. TRIPOD
Prior GDM
236
2.5
Troglitazone
55%
Sweden XENDOS
IGT or NGT
3305
4.0
Orlistat +
diet/exercise
45%
Canada DREAM
IGT
4894
3.0
Rosiglitazone
58%
Canada CANOE
IGT
207
3.9
Rosiglitazone +
metformin
66%
EU/Can Stop-NIDDM
IGT
1429
3.3
Acarbose
25%
ACT NOW = Actos Now for the prevention of diabetes; TRIPOD = TRoglitazone in the
Prevention Of Diabetes; XENDOS = XENical in the prevention of diabetes in obese
subjects; DREAM = Diabetes REduction Assessment with rampiril and rosiglitazone
Medication; CANOE = CANadian Normoglycemia Outcomes Evaluation
Diabetes Prevention Studies Overview:
Lifestyle Modification
Study
Subjects
Total N
Followup (y)
Intervention
Diabetes
Risk ↓
US DPP
IGT
3234
2.8
Diet + exercise
58%
China
Da Qing
IGT
530
6.0
Diet
Exercise
Diet + exercise
35%
39%
32%
Finland DPP
IGT
522
3.2
Diet + exercise
52%
India DPP
IGT
531
2.5
Diet + exercise
29%
Japan DPP
IGT
458
4.0
Diet + exercise
67%
Spain
PREDIMED
CHD risk
factors (≥3)
418
4.0
Olive oil- or
Nut-based
Mediterranean
diet
43%
39%
CHD = coronary heart disease
DPP = Diabetes Prevention Program
PREDIMED = Prevención con Dieta Mediterránea
Diabetes Prevention Program
Lifestyle Targets: 7% Weight Loss, 150 min/wk Activity
DPP N Engl J Med 2002; 346:393-403.
Effect of Lifestyle Changes (Diet and Exercise)
on Incidence of T2DM
 A review of studies of 4864 high-risk individuals followed for 2.5-6 y
reported
– Lifestyle changes may lower incidence of T2DM by 28-59%
– 6.4 individuals need to be treated to prevent or delay 1 case of diabetes
through lifestyle changes (over 3-4 years)
– Various weight loss diets (low fat, high protein, or Mediterranean) may be
effective (weight loss more important than how achieved)
– Maintenance of weight loss requires regular exercise with additional
expenditure of ~2000 kcal/week (~15 miles of walking)
Walker KZ, et al. J Hum Nutr Diet. 2010;23:344-352.
Meta-Analysis: Estimates of Associations
Between Macronutrient Intake and T2DM Risk
CHO analysis: 10 cohort studies; fat analysis: 14 cohort studies; protein analysis: 4 cohort studies
Macronutrient
Relative Risk
95% Confidence
Interval (CI)
Carbohydrate*
1.11
1.01, 1.22
Fat
0.93
0.86, 1.01
0.76
0.68, 0.85
1.02
0.91, 1.15
Vegetable Fat†
Protein
* A high vs. low intake of total CHO was associated with higher risk of T2DM (p = 0.035).
† A high vs. low intake of vegetable fat was associated with lower risk of T2DM (p < 0.001).
Alhazmi A, et al. J Am Coll Nutr. 2012;31:243-258.
Risk of Developing T2DM Associated with
Increased Glycemic Index and Load
Results for glycemic load were similar to those for glycemic index.
Glycemic load is affected by carbohydrate intake and glycemic index.
Barclay AW, et al. Am J Clin Nutr. 2008;87:627-637.
Dietary Fibers and Diabetes Risk
Schulze et al. Arch Intern Med 2007;167:956-965.
Nurses Health Study: Relative Risk of T2DM by
Different Levels of Cereal Fiber and Glycemic Load
Salmeron J, et al. JAMA. 1997;227:472-477.
Resistant Starch Intake Increases Insulin
Sensitivity in Overweight and Obese Men
HAM-RS2 = high-amylose maize type 2 resistant starch
SI = insulin sensitivity
Maki KC, et al. J Nutr. 2012;142:717-723.
Effect of Short-Term (24 hr) Resistant Starch
Consumption on Breath H2 and FFA (NEFA)
Closed symbols are control and
open symbols are resistant starch
Robertson MD, et al. Diabetologia. 2003;46:659-665.
Fermentable Dietary Fiber and Insulin
Sensitivity
Sleeth et al. Nutrition Research Reviews 2010;23:135–145
Food Sources of Fermentable Fibers
 Oats and barley (beta-glucan)
 Prunes, apples and pears (pectin)
 Nuts and seeds
 Legumes
 Multi-grain breads (those with ≥3 g fiber per slice)
Sugar Sweetened Product Consumption
Reduce Insulin Sensitivity
Parameter
Baseline
Dairy (Δ)
SSP (Δ)
Difference P-value*
Mean (SEM) or Median (Q1, Q3)
4.16
-0.10
-0.49
MISI
HOMA2-%S
(2.81, 5.98)
117.8
(-0.96, 0.54)
1.3
(-1.01, 0.14)
-21.3
(86.2, 147.1)
(-21.3, 29.3)
(-33.1, -3.30)
0.39
0.290
22.6
0.009
Dairy = 2 servings per day of 2% milk and 1 serving of yogurt
SSP = 2 servings per day of sugar-sweetened cola and 1 serving of non-dairy pudding
Maki et al. Experimental Biology 2014
Abbreviations: AUC, area under the curve; HOMA2-%B, homeostasis model assessment 2-β-cell
function; HOMA2-%S, homeostasis model assessment 2-insulin sensitivity Matsuda insulin sensitivity
index; SSP, sugar-sweetened products.
*P-values were calculated from a repeated measures ANCOVA model between dairy and SSP conditions
(N = 34).
Differences in Lipids and 25-OH Vitamin D Between
Dairy and Sugar-sweetened Product Conditions
Parameter*
Baseline
(mg/dL)
Dairy (%Δ)
SSP (%Δ)
Difference
P-value*
Mean (SEM) or Median (Q1, Q3)
LDL-C
125.7 (5.82)
-0.0 (2.2)
-0.1 (2.2)
0.1
0.947
Non-HDL-C
153.4 (6.95)
-0.4 (2.0)
0.5 (2.2)
-0.9
0.752
TC
196.7 (6.81)
-0.6 (1.5)
-0.7 (1.5)
0.1
0.953
44.3 (1.53)
0.8 (2.0)
-4.2 (1.3)
5.0
0.015
133.2 (7.33)
-2.0 (4.7)
6.0 (4.6)
-8.0
0.209
24.5 (2.2)
11.7 (5.6)
-3.3 (3.4)
15.0
0.022
HDL-C
Triglycerides
25(OH)D
(ng/mL)
Abbreviations: -C, cholesterol; HDL, high-density lipoprotein, LDL, low-density lipoprotein; SSP,
sugar-sweetened products; TC, total cholesterol.
*P-values were calculated from a repeated measures ANCOVA model between dairy and SSP conditions
(N = 34).
Dietary Macronutrient Composition
and T2DM Risk
 Macronutrient changes and T2DM risk
 Reduce intakes of foods high in refined carbohydrates (CHO)

Sugars and refined starches
 Potential options for substitution

CHO-rich foods with low glycemic index, particularly whole grains that
contain cereal and fermentable fibers

Fats (particularly vegetable fats)

Proteins

Alcohol
High Cereal Fiber or Moderate Cereal Fiber and
Moderate Protein Diet Improves Insulin Sensitivity
Nutrient
Control
High cereal
fiber (HCF)
High PRO
(HP)
Mix
CHO, % energy
55
55
40-45
45-50
PRO, % energy
15
15
25-30
20-25
Fat, % energy
30
30
30
30
Dietary fiber, g
~20
~50
~20
~35
Values are % of baseline, 3 = sig diff from HP, 4 = sig diff from baseline
N = 111 overweight adults; M value = insulin-mediated glucose uptake as a
measurement of whole-body insulin sensitivity; EGP = endogenous glucose production
Weickert MO, et al. Am J Clin Nutr. 2011;94:459-471.
Meta-Analysis of 74 Trials of High Protein
vs. Lower Protein Diets on Health Outcomes
Santesso N, et al. Eur J Clin Nutr. 2012;66:780-788.
Potential Mechanisms for Higher Protein
Diets and Weight Loss
Hu FB. Am J Clin Nutr. 2005;82 (suppl):242S-247S.
Energy Expenditure Higher After
Protein vs. CHO Intake
Acheson et al., Am J Clin Nutr 2011;93:525-534
Appetite Visual Analog Scale Ratings
Following Low vs. High Protein Breakfasts
N = 34 healthy women; randomized controlled crossover trial
30 and 39 g protein produced greater appetite control throughout the morning vs. NB and LP (p < 0.001)
LP = low protein breakfast (3 g protein), NB = no breakfast (water only)
Rains TM, et al. Poster presented at The Obesity Society. November, 2013.
Energy Intakes at Lunch Following Low vs.
High Protein Breakfasts
N = 34 healthy women; randomized controlled crossover trial
LP = low-protein breakfast (3 g protein), NB = no breakfast (water only)
Different letters indicate significant difference (p < 0.05);
energy intake at lunch for 30 g Pro vs. LP was p = 0.053
Rains TM, et al. Poster presented at The Obesity Society. November, 2013.
Effect of a Reduced Glycemic Load Diet (Lower
CHO, Higher Protein and Fat) on Weight Loss
♦ Control diet (low-fat, portion control – 46/19/37% CHO/PRO/Fat)
■ Reduced glycemic load diet (32/26/42% CHO/PRO/Fat)
Maki KC, et al. Am J Clin Nutr. 2007;85:724-734.
POUNDS LOST: All Diets Resulted in Clinically
Meaningful Weight Loss, But…
Macronutrient intake targets at 6 and 12 months were not met
N = 811 overweight adults
Sacks FM, et al. N Engl J Med. 2009;360:859-873.
POUNDS LOST: Targeted Differential PRO
Intake Was Not Achieved
Intake/d
Low Fat/
Average PRO
Low Fat/
High PRO
High Fat/
Average PRO
High Fat/
High PRO
6 mo
2y
6 mo
2y
6 mo
2y
6 mo
2y
CHO, %
57.5
53.2
53.4
51.3
49.1
48.6
43.0
42.9
PRO, %
17.6
19.6
21.8
20.8
18.4
19.6
22.6
21.2
Fat, %
26.2
26.5
25.9
28.4
33.9
33.3
34.3
35.1
Targets
Sacks FM, et al. N Engl J Med. 2009;360:859-873.
Protein and Glycemic Index in Weight Loss
Maintenance
 548 participants
completed the study
 Results suggest that the
high-protein, low
glycemic index diet may
help to reduce weight
regain, although the effect
was modest (3-4 lb)
LP = low protein (13% en)
HP = high protein (25% en)
LGI = low glycemic index
HGI = high glycemic index
Larsen TM, et al. N Engl J Med. 2010;363:2102-2113.
Optimal Macronutrient Intake Trial to
Prevent Heart Disease (OmniHeart)
N = 164 individuals with prehypertension or stage 1 hypertension without diabetes
Each feeding period lasted 6 wks, and body weight was kept stable
Targets (% kcal)
CARB
PROT
UNSAT
CHO
58
48
48
PRO
15
25
15
Fat
27
27
37
MUFA
13
13
21
PUFA
8
8
10
SFA
6
6
6
CARB: carbohydrate-rich diet similar to Dietary Approaches to Stop Hypertension
PROT: replacement of 10% of CHO calories with PRO (mixed source)
UNSAT: replacement of 10% of CHO calories with unsaturated fats
MUFA = monounsaturated fatty acids
PUFA = polyunsaturated fatty acids
SFA = saturated fatty acids
Appel LJ, et al. JAMA. 2005;294:2455-2464.
OmniHeart: Results for Measures of Insulin
Sensitivity
Baseline
(BL)
Mean
UNSAT
vs CARB
PROT
vs CARB
UNSAT
vs PROT
Mean (95% CI) between-diet  from BL
QUICKI
0.35
0.005*
(0.000, 0.009)
1/HOMA-IR
0.74
0.11*
(0.03, 0.20)
0.001
(-0.004, 0.007)
0.003
(-0.002, 0.009)
0.04
(-0.07, 0.14)
0.08
(-0.05, 0.20)
*p < 0.05 (for 1/HOMA-IR the increase compared to CARB was ~15%)
QUICKI = quantitative insulin sensitivity check
1/HOMA = homeostasis model assessment of insulin resistance reported as the reciprocal
Gadgil MD, et al. Diabetes Care. 2013;36:1132-1137.
Other Dietary Factors Associated with Lower Risk
of T2DM – Need More Research Before Specific
Recommendations
 Coffee
– Especially in place of sugar-sweetened beverages
 Polyphenols
– Found in some foods and beverages
– Berries, cherries, cranberries, coffee, tea, cocoa
 Cinnamon
– High doses of cinnamaldehyde
 Magnesium
– High levels in whole grain foods
 Chromium
 Dairy foods (esp. fermented dairy products)
 Moderate alcohol consumption
Dietary Supplements and Diabetes
 Despite an increasing body of literature
investigating the use of natural [dietary]
supplements on the treatment of diabetes, the
American Diabetes Association (ADA) does not
recommend their use because:
– Clinical evidence showing efficacy is insufficient
– Standardized formulations are [often] lacking
Allen RW. Ann Fam Med. 2013;11(5):452-459
Theoretical Causal Model for Effects of
Coffee on Risk of T2DM
COFFEE
Chlorogenic acids
Trigonelline
Quinides
Micronutrients
GUT
GIP
GLP-1
Glusose
absorption
Iron
LIVER
absorption
G-6-Pase
Gluconeogene
sis
Inflammation
Oxidativ
e stress
β-cell
function
Glycemic control
Insulin
resistance
T2D
Coffee Intake and Reduced Risk of T2DM:
Potential Mechanisms?
 Anti-inflammatory (Frost Anderson, Jacobs, et al. AJCN 2006)
– Coffee is a rich source of minerals and phytochemical compounds,
including phenolics, that may confer protection from systemic
inflammation

Systemic inflammation has been found to predict type 2 diabetes
independent or traditional risk factors
 Antioxidants (Svilaas et al., J Nutr 2004)
– Coffee is a rich source of antioxidant compounds, may confer
protection from oxidative stress

Oxidative stress is elevated in obesity and type 2 diabetes
Polyphenols
 Natural phytochemical compounds in plant-based foods (such as fruits,
vegetables, whole grains, cereal, legumes, tea, coffee, wine and cocoa)
 More than 8000 polyphenolic compounds have been identified
 Several biological activities and benefits have been documented:
–
Examples include:




Antioxidant
Anti-allergic
Anti-inflammatory
Anti-viral / anti-microbial
 May modulate important cell signaling ways:
–
Examples include:



Nuclear factor kappa-β (NF-κβ)
Activator protein-1 DNA binding (AP-1)
Extracellular signal-related protein kinase (ERK)
Bahadoran Z. J Diab Met Disor. 2013;12:43-52
Polyphenols: 2 Major Categories
 Phenolic Acids (1/3 of polyphenolic compounds in diet)
– Hydroxybenzoic acid derviatives



Protocatechuic acid
Gallic acid
p-hydroxybenzoic acid
– Hydroxycinnamic acid derivatives





Caffeic acid
Chlorogenic acid
Coumaric acid
Ferulic acid
Sinapic acid
 Flavonoids (the most abundant polyphenols; more than 4000 types
identified)
–
–
–
–
–
–
Anthocyanins
Flavonols
Flavanols
Flavanones
Flavones
Isoflavones
Examples of Food Sources of Polyphenols
 Phenolic acids
–
–
–
–
–
–
–
Berry fruits
Kiwi
Cherry
Apple
Pear
Chicory
Coffee
 Flavonoids
– Anthocyanins: berries
family, red wine, red
cabbage, cherry, black
grape, strawberry
– Flavonols: onion, curly
kale, leeks, broccoli,
blueberries
– Isoflavones: soybeans
and soy products
Cinnamon
 Hypothesized to provide health benefits, such as lowering serum
lipids and blood glucose
 Proposed active component: cinnamaldehyde
–
Insulinotropic effects have been investigated, thought to be responsible for:




Promoting insulin release
Enhancing insulin sensitivity
Increasing insulin disposal
Exerting activity in the regulation of protein-tyrosine phosphatase 1β (PTP1β ) and insulin
receptor kinase
 Results of 2013 systematic review and meta-analysis evaluating the
effects of cinnamon on glycemia and lipid levels:
–
Statistically significant reductions in fasting plasma glucose, total cholesterol, LDLcholesterol, and triglycerides; statistically significant increase in HDL-cholesterol
–
No effect on hemoglobin A1c
Allen RW. Ann Fam Med. 2013;11(5):452-459
Magnesium
 Prospective studies  those with higher Mg intake are 10-47% less likely to develop T2DM
–
Only 50% of Americans (1 yr+) achieve recommended dietary allowance for Mg (400-420 mg/day for
adult men & 300-310 mg/day for adult women)
 Results from several clinical trials (short duration, ≤ 6 months) of Mg in those
with and without diabetes found that supplementation may improve:
–
Glycemic control, insulin sensitivity, beta-cell function



Randomized, placebo-controlled trial in obese, nondiabetic, insulin-resistant subjects  6 months of 365 mg/day
Mg significantly lowered fasting glucose, fasting insulin, insulin resistance and improved insulin sensitivity
Three-month supplementation of Mg in subjects with other risk factors (such as mild hypertension or
hypomagnesemia) found to improve insulin sensitivity and pancreatic β-cell function
Low-Mg diets given to healthy subjects has been shown to impair insulin sensitivity after 3 weeks
 Experimental evidence from animal studies supports association between Mg and insulin
sensitivity:
–
Animals fed Mg-deficient diets  insulin sensitivity of peripheral tissues is reduced via decrease
autophosphorylation of tyrosine kinase (a component of the β-subunit of the insulin receptor, which Mg
is a cofactor)
Hruby A. Diab Care. 2014;37:419-427
Chromium
 Chromium deficiency may aggravate carbohydrate intolerance
 Late 1990’s, two randomized, placebo-controlled studies in China found
that chromium supplementation had beneficial effects on glycemia
 Results from small studies indicate that chromium may have a role in:
–
Glucose intolerance
–
Gestational diabetes
–
Corticosteroid-induced diabetes
 American Diabetes Association stated that benefit from chromium
has not been clearly demonstrated, therefore, chromium
supplementation in individuals with diabetes or obesity can not be
recommended
Cefalu WT. Diab Care. 2004;27(11):2741-2751
Dairy Foods
 2010 Dietary Guidelines for Americans: “Moderate
evidence…indicates that intake of milk and milk products is
associated with a reduced risk of cardiovascular disease and type 2
diabetes and with lower blood pressure in adults.”
 Potential mechanisms of action
– Dairy foods are important sources of nutrients:





Calcium – increases insulin secretion; is essential for insulin-responsive tissues (i.e.,
skeletal muscle and adipose tissue) and may reduce insulin resistance
Vitamin D – associated with decreased risk of diabetes, possibly by influencing insulin
secretion and decreasing insulin resistance
Whey protein – reduce body weight gain in animal models
Magnesium – associated with reduced diabetes risk (in epidemiologic studies) and with
improved insulin sensitivity in some experimental studies but data are limited
Fat – trans-palmitoleic acid, a biomarker of dairy fat, was inversely associated with risk of
type 2 diabetes, suggests possible protective effect of specific milk-fat components
Aune D. Am J Clin Nutr. 2013;98(4):1066-1083
Moderate Alcohol Consumption
 Results of meta-analysis: ~30% reduced risk of type 2
diabetes with moderate alcohol consumption
 Proposed mechanisms of action with moderate use:
– Increased HDL cholesterol
– Anti-inflammatory effect
– Enhanced insulin sensitivity with lower plasma insulin
concentrations
Koppes LLJ. Diab Care. 2005;28(3):719-725
Characteristics of a Low-Risk
Dietary Pattern
Maki KC, et al. AJC. 2004;93(11A):12C-17C.
Conclusions
 Metabolic syndrome is a cluster of risk factors for both T2DM and
cardiovascular disease that cluster together and are related to
insulin resistance.
 T2DM results from a combination of metabolic defects including
insulin resistance in skeletal muscle and liver, pancreatic betacell dysfunction, and excessive adipose tissue lipolysis.
 Results from intervention trials with weight loss + exercise and a
Mediterranean diet intervention, as well as pharmaceutical
interventions, show that T2DM can be prevented or delayed in
those with pre-diabetes.
 A diet high in carbohydrate, particularly refined (high GI)
carbohydrate, is associated with increased risk for T2DM.
Conclusions
 Substituting foods high in refined carbohydrate with
alternatives tends to improve the T2DM/metabolic
syndrome risk factor profile
 Substitutions which show the greatest promise and which
warrant further research include:
– Carbohydrate-rich foods


Low glycemic index
High in cereal and fermentable fibers (improved insulin sensitivity)
– Protein-rich foods

Mainly related to appetite and weight effects
– Vegetable (unsaturated) fats
– Foods high in polyphenols, fermented dairy products, moderate
alcohol in those who drink

No more than 14 drinks per week for men and 7 per week for women