Eat Chocolate, Stay Slim!
Chocolates certainly strike the fancy of one and all; age is no barrier to it whatsoever. Since long, the advantages of eating chocolates have been shared by dieticians and medical experts.
Along the same lines, it has been revealed recently that people who eat chocolates on a regular basis generally have a tendency of being thinner than those who eat chocolates seldom.
In this regard, a recently concluded study, which was carried out by a team of researchers from the University of California in San Diego, has revealed that the outcomes of the study which took into account more than 1,000 US citizen focused on the aspects of diet, calorie consumption and Body Mass Index (BMI) – which is said to be a measure of obesity.
During the course of the study, the researchers successfully found that those who consume chocolate just a few times weekly were, in general, much slimmer as compared to people who consumed chocolates on occasions.
Though chocolate is full of calories, it has various ingredients which may well result in favoring weight loss instead of inspiring fat synthesis, as claimed by the team of scientists.
The findings of the study, which have been made available in the recent edition of the Archives of Internal Medicine, have further revealed that regardless of providing a boost in terms of calorie intake, regular consumption of chocolate can easily be related to a reduced BMI.
While expressing his opinion regarding the findings of the study, Dr Beatrice Golomb, the lead author at the University of California, San Diego, claimed: “Our findings appear to add to a body of information suggesting that the composition of calories, not just the number of them, matters for determining their ultimate impact on weight”.
The link remained even when other factors, like how much exercise individuals did, were taken into account. And it appears it is how often you eat chocolate that is important, rather than how much of it you eat. The study found no link with quantity consumed.
According to the researchers, there is only one chance in a hundred that their findings could be explained by chance alone.
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