Chocolate has shown favorable metabolic associations with blood pressure (BP),1–3 insulin sensitivity,1 and cholesterol level.3 Chocolate is rich in antioxidant phytonutrients like catechins that could contribute to favorable relationships of chocolate consumption to insulin sensitivity and BP. However, because chocolate is often consumed as a sweet and bears calories, there are concerns related to its intake.
Body mass index (BMI) is part of the metabolic syndrome (MetS) picture, and other MetS elements relate favorably to moderate chocolate consumption. Therefore, we hypothesized that the benefits of modest frequent chocolate intake might extend to reduced fat deposition, potentially offsetting the added calories. To evaluate this, we examined the cross-sectional relationship of chocolate consumption frequency to BMI.
Methods
Subjects
A total of 1018 men and women aged 20 to 85 years from San Diego, California, without known cardiovascular disease, diabetes, or extremes of low-density lipoprotein cholesterol (LDL-C) levels (115–190 mg/dL inclusive [to convert to millimoles per liter, multiply by 0.0259]), were screenees for participation in a broadly sampling clinical study examining noncardiac effects of statins.4,5 The study protocol was approved by the University of California, San Diego Human Research Protections Program; all participants gave written informed consent.
Measures
To measure chocolate consumption frequency, 1017 subjects responded to the question “How many times a week do you consume chocolate?” Body mass index (calculated as weight in kilograms divided by height in meters squared) was determined for 972 subjects (95.6%), who had both weight and height recorded at the screening visit.
Of the subjects, 975 (95.8%) completed the validated Fred Hutchinson Food Frequency Questionnaire (FFQ). Calories (determined via FFQ) could mediate associations of chocolate with BMI (contravening calorie adjustment): analyses were performed with and without calorie adjustment. Fruit and vegetable intake and saturated fat (satfat) intake were assessed for relevance. Fruits and vegetables (linked to lower BMI) bore no relationship to chocolate consumption frequency (β = 0.004 [SE = 0.007]; P = .55), excluding this as a candidate confounder, but satfats (which, however, accompany chocolate via stearic acid) were significantly related both to chocolate intake (β = 0.035 [SE = 0.005]; P < .001) and higher BMI. Analyses were performed with and without satfat adjustment. Amount of chocolate consumed (vs frequency with which it was consumed) was also examined. This was determined from the FFQ.
Activity was assessed as how many times per 7-day period the subject engaged in vigorous activity for at least 20 minutes (heart beating rapidly). To evaluate mood, subjects completed the Center for Epidemiological Studies Depression scale (CES-D). Chocolate consumption in this sample was previously associated unfavorably with mood.6 Because mood could serve as a confounder or mediator, analyses were conducted with and without CES-D adjustment.
Statistical Analysis
Univariate summary statistics and bivariate relationships to chocolate and BMI were assessed. Linear regression analysis with standard errors as developed by White7 (heteroskedasticity independent or “robust” standard errors) was used to evaluate chocolate consumption frequency as a predictor of BMI in unadjusted models, in age- and sex-adjusted models, and in models adding adjustment for activity, satfats, and mood. Though the appropriateness of calorie adjustment is debatable (as a variable potentially on the causal pathway to BMI), analyses adjusting for calories were included. Analyses used Stata versions 8.0 and 11.0 (StataCorp). A 2-sided P value of <.05 was considered significant.
Results
The mean (SD) age of the subjects was 57 (12) years and 68% were male, with a mean (SD) BMI of 28 (4.5). Subjects ate chocolate a mean (SD) 2.0 (2.5) times/wk and exercised 3.6 (3.0) times/wk. Chocolate consumption frequency was linked to greater calorie and satfat intake and higher CES-D scores (all P < .001), each relating positively to BMI. Chocolate consumption frequency was not linked to greater activity (P = .41). Yet, greater chocolate consumption frequency was linked to lower BMI (unadjusted, P = .01).
Chocolate preserved its relation to lower BMI with age and sex adjustments (Table)—and indeed, in a range of adjustment models adding activity, calories, satfats, and CES-D score. Calories, satfats, and depression could serve mediating rather than confounding roles. However, chocolate consumption frequency predicted lower BMI with or without such adjustment.
Table.
Chocolate Consumption Frequency Predicts Lower BMI: Regression Resultsa
| Chocolate Consumption Frequency, Association With BMI |
||
|---|---|---|
| Adjustment Model | β (SE) | P Value |
| Unadjusted | −0.142 (0.053) | .008 |
| Age and sex adjusted | −0.126 (0.053) | .02 |
| Age, sex, and activity adjusted | −0.130 (0.052) | .01 |
| Age, sex, activity, and calorie adjusted | −0.146 (0.059) | .01 |
| Age, sex, activity, and satfat adjusted | −0.190 (0.059) | .001 |
| Age, sex, activity, satfat, and CES-D adjusted | −0.191 (0.059) | .001 |
| Age, sex, activity, satfat, fruit and vegetable, and CES-D adjusted | −0.201 (0.060) | .001 |
| Age, sex, activity, satfat, fruit and vegetable, CES-D, and calories adjusted | −0.208 (0.060) | .001 |
Abbreviations: BMI, body mass index; CES-D, Center for Epidemiological Studies Depression scale; satfat, saturated fat.
A model containing calories (and activity, as well as age and sex) was included, since calories and activity are usual predictors of BMI. However, calories were otherwise not in adjustment models because chocolate inherently contains calories and adjustment could justly be deemed inappropriate—overstating the benefits of chocolate to BMI. Closely similar results were obtained using an alternate activity measure. Significance was identical for all except the third and fourth models, where significance was stronger (P = .006 and P = .007, vs P = .01 and P = .01).
A chocolate consumption frequency–squared term was nonsignificant, providing no evidence for a U-shaped relationship of chocolate consumption frequency to BMI. In contrast to chocolate consumption frequency, the amount of chocolate eaten was not related to BMI, favorably or adversely (eg, per medium chocolate serving or 1 oz [28 g], β = 0.00057 [P = .97] in an age- and sex-adjusted model [analyses not shown]).
Comment
Adults who consumed chocolate more frequently had a lower BMI than those who consumed chocolate less often. The findings were retained or strengthened in a range of adjustment models and was not explained by calorie intake (frequent chocolate intake was linked to more overall calories), activity, or other assessed potential confounders.
The connection of higher chocolate consumption frequency to lower BMI is opposite to associations presumed based on calories alone, but concordant with a growing body of literature suggesting that the character—as well as the quantity—of calories has an impact on MetS factors. Chocolate has shown other metabolic benefits—in prospective observational studies2 and randomized trials—in regard to insulin sensitivity,1 BP,1,2 and total and LDL-C levels.3 (Chocolate has also been linked in prospective observational studies to lower cardiovascular and all-cause mortality,2 outcomes predicted by MetS elements.) Thus, our findings extend favorable associations of chocolate to metabolic factors.
Chocolate products are often rich in sugar and fat, contributing to assumptions that chocolate boosts BMI. This study does not obviate the possibility that some chocolate-containing products do so, that some chocolate consumption profiles do so, or that for some people, even frequent modest chocolate consumption does so. Moreover, since findings are cross-sectional, causality in the observed association cannot be presumed. However, the finding fits with the literature suggesting benefits of chocolate for other metabolic factors, and we failed to identify a link of chocolate to key BMI-relevant confounders in a direction to explain the finding. Moreover, our findings comport with recent findings from experimental frequent feeding of modest doses of epicatechin from chocolate to rats.8,9 Polyphenols (eg, catechins) in chocolate1 have antioxidant properties and are candidates to underlie favorable chocolate associations with metabolic factors. Cocoa-derived epicatechin, specifically, is reported to increase mitochondrial biogenesis and capillarity, muscular performance, and lean muscle mass and to reduce weight without changing calories or exercise in rodent studies.8,9 Parallel processes in humans, if present, could underlie our findings.
In conclusion, our findings—that more frequent chocolate intake is linked to lower BMI—are intriguing. They accord with other findings suggesting that diet composition, as well as calorie number, may influence BMI. They comport with reported benefits of chocolate to other elements of MetS. Compatible experimental findings in rats given epicatechin from cocoa suggest the association could be causal. A randomized trial of chocolate for metabolic benefits in humans may be merited.
Acknowledgments
Funding/Support: This study was funded by grant RO1 HL63055 from the National Heart, Lung, and Blood Institute, National Institutes of Health (NIH), and was supported by the University of California, San Diego General Clinical Research Center (NIH # MO1 RR00827).
Role of the Sponsors: The funding source did not influence the design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, or approval of the manuscript.
Footnotes
Author Contributions: All authors had full access to the data (statistical printouts validating each finding were shared) and take responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: Golomb and White. Acquisition of data: Golomb. Analysis and interpretation of data: Golomb, Koperski, and White. Drafting of the manuscript: Golomb and White. Critical revision of the manuscript for important intellectual content: Golomb and Koperski. Statistical analysis: Golomb and White. Obtained funding: Golomb. Administrative, technical, and material support: Koperski.
Financial Disclosure: All authors declare that they have no conflicts of interest to disclose but profess an anti-conflict via their chocolate purchasing habits.
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