School of Medicine, Health Sciences and Engineering Susquehanna Township High School Lecture Series Week 23, February 4 2014 Clinical Relevance of This Week s Topic Metabolic Factors Frequency of Chocolate Consumption and Body Mass Index Wen Jie Zhang, MD, PhD Professor of Pathology
Transformation among Carbohydrates, Fats, and Proteins (Breads/Donuts, Cheese/Butter, Beef/Pork) Carbs (glucose) Catabolism Anabolism Fat (Fatty acids) Protein (Amino acids)
Investigation on Chocolate Consumption and BMI Association Between More Frequent Chocolate Consumption and Lower Body Mass Index Beatrice A. Golomb, MD, PhD Sabrina Koperski, BS Halbert L. White, PhD Archives of Internal Medicine, Volume 172, No. 6: 519-520, 2012
Background Chocolate has shown favorable metabolic associations with: Blood pressure (BP) Insulin sensitivity (lower blood sugar) Cholesterol
Hypothesis Chocolate is often consumed as a sweet and bears calories, there are concerns related to its intake Hypothesis: The benefits of modest frequent chocolate intake might extend to reduced fat deposition, potentially offsetting the added calories
Methods Subjects: 1018 men and women Ages: 20 to 85 years Community: San Diego, California With no known medical conditions: cardiovascular disease Diabetes or extremes of low-density lipoprotein cholesterol (LDL-C) levels (115-190 mg/dl)
Measurements Question: 1017 subjects responded to the question How many times a week do you consume chocolate? Measurements: Body Mass Index (BMI) Fruit, vegetable, and saturated fat intake Calories Fred Hutchinson Food Frequency Questionnaire (FFQ)
Measurements (cont d) Physical activity how many times per 7-day period the subject engaged in vigorous activity for at least 20 minutes (heart beating rapidly) Mood Center for Epidemiological Studies Depression scale (CES-D) measurement (mood may serve as a confounding factor)
Results (1) Mean (with Standard Deviation or SD) age of the subjects 57 yrs (SD=12) and 68% were male Mean BMI 28 kg/m2 (SD=4.5) Mean chocolate consumption frequency 2.0 times/week (SD=2.5) Mean activity 3.6 times/week (SD=3.0)
Results (2) Chocolate consumption frequency was linked to: (all P<0.001) Greater calorie intake (positively related to BMI) Saturated fat intake (positively related to BMI) Higher CES-D scores (positively related to BMI) However, chocolate consumption frequency was not linked to greater activity (P=0.41)
Results (3) Greater chocolate consumption frequency was linked to lower BMI (unadjusted, P=0.01) Chocolate consumption frequency preserved its relation to lower BMI with age and sex adjustments (Table) and indeed, in a range of adjustment models adding activity, calories, saturated fats, and CES-D score.
Table
Results (4) In contrast, the amount of chocolate eaten was not related to BMI, favorably or adversely (e.g., per medium chocolate serving or 1 oz [28 g] in an age- and sex-adjusted model)
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Discussion Thus, the findings extend favorable associations of chocolate to metabolic factors (BMI) Polyphenols (e.g., catechins are abundant in teas and cocoas, and also present in fruits, vegetables, and wine) have antioxidant properties and are candidates to underlie favorable chocolate associations with metabolic factors
Risk Factors of Metabolic Syndrome Complex and under investigation Older age (most patients but many young adults) Overweight and obesity (BMI-based) Sedentary (inactive) behavior Diet (sugar-sweetened beverage, e.g., Coke) Stress Genetics Schizophrenia (32% and 51% patients meet MS criteria) Molecules: Fibrinogen, interleukin 6, tumor necrosis factor-α, C-reactive protein, etc.
Supporting Evidence Chocolate has shown other metabolic benefits Increased insulin sensitivity Lower blood pressure Lower total and LDL-cholesterol Lower cardiovascular and all-cause mortality experimentally frequent feeding of modest doses of epicatechin from chocolate to rats
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Probability (P) Values In statistics, a result is called statistically significant if it has been predicted as unlikely to have occurred by chance alone, according to a pre-determined threshold probability, the significance level. A significance level is usually P<0.05 (<5%)
Confounding Factors In statistics, a confounding factor (also confounding variable, lurking variable, confound, or confounder) is an extraneous variable in a statistical model that correlates (positively or negatively) with both the dependent variable and the independent variable
Types of Epidemiologic Studies Retrospective study Prospective study
The End
Epidemiology of Metabolic Syndrome In the US: 34% of the adult population In the World: (US, Europe, India) >25% of adults In China: 13.2% of adult urban population (Han ethnic majority) Kazakh ethnic population in Xinjiang: 33%
Major Associated Diseases with MS Cardiovascular diseases, particularly coronary heart disease Type 2 diabetes (diabetes mellitus type 2)
Treatment of MS The first line treatment is change of lifestyle Diet, physical activity If no improvement in 3-6 months, the individual disorders that compose the metabolic syndrome are treated separately