6 Responses to “Chocolate ‘may help keep people slim’ (not)!”

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  1. avatar Nadine says:

    Perhaps the fatter people underestimated their chocolate consumption?

  2. avatar Zoë says:

    Hi Nadine – Good point! I did a Radio 5 live interview on this on Tuesday and the doctor in the studio made the same point. I am quite happy to confess to my daily chocolate consumption, but then, with a BMI of 20-21, I am unlikely to be judged as fat and greedy for eating a bar of 85-90% daily. Would I be so keen to do this if I had a BMI of 29? Probably not. Overweight people already say they feel guilty and uncomfortable eating in public, as they feel that they are being judged. Would this impact declarations of consumption – quite probably.
    Nice one!
    Very best wishes – Zoe

  3. avatar Steve Kass says:

    Hi Zoë,

    You write

    The Beta coefficient (β) is as follows:

    For unadjusted data β = -0.142
    Adjusted for age/gender β = -0.126
    Adjusted for age/gender/exercise/fat/fruit/veg intake/depression scale & calorie intake! β = -0.208

    This is tiny. I appreciate that beta coefficients have been used because the units of the two variables are substantially different (BMI vs frequency of consumption). However, had the Pearson correlation method resulted in a correlation of -0.142 (r=-0.142), the r squared would be 0.02. We would interpret this r squared to mean that 2% of the variability in BMI may be accounted for by frequency of chocolate consumption. This hardly justifies world headlines.

    You seem to be suggesting that the Beta coefficient for the unadjusted data would equal the Pearson’s correlation coefficient and allow an estimate of the variability in BMI attributable to the frequency of chocolate consumption.

    This isn’t right. The Beta coefficient is the slope of the best fit line through the scatterplot of BMI v. chocolate-eating frequency. Pearson’s, on the other hand, represents how tightly clustered along the best fit line the scatterplot points are. How well the points cluster along the line indicates what percentage of BMI variation can be accounted for by chocolate consumption frequency. The slope of the line doesn’t provide any information about this percentage.

    It’s possible to have a very large slope (Beta) and a correlation (Pearson’s) near zero, or vice versa – small slope but strong correlation. (The slope, but not Pearson’s, depends on units. If consumption were measured in times per month instead of per week, the slope would go down by a factor of four, but Pearson’s would not change at all.)

    The slope (Beta) simply indicates how big a decrease in BMI was observed for each additional time per week chocolate was consumed. It doesn’t, however, tell how reliable or consistent this association was – it’s only an average. (In this study, each additional time per week was associated with a drop in BMI of 1/5 of a point, on average, which is a very small change. Without more information, the range of BMI differences might have been wide, with some increases and some decreases, or it could have been consistently near 1/5.)

    I suspect you’re right that the effect here is not very meaningful, but you can’t use Beta to guess the percent of BMI variation due to chocolate-eating frequency.

  4. Nadine, why does it always seems that all dietitians/nutritionist are accusing fat people of lying?
    The problem is carbohydrates. Eat 44 g fat (=400 kcal) and you are satified for at least 4 hours.
    Eat 100 g carbohydrates (=400 kcal) and 50 g are transformed into 10 g fat and stored. This means that after 2 h the blood glucose level will plummet and you are forced to eat another 100 g glucose to stay alive for another two hours and store another 10 g fat.

    So in the latter case you are forced by your own body to “overeat” those extra 100 g carbohydrates.

    By eating real animal fat you are always satified and the fat has less than 50% saturated fats, less than 50 % MUFA and normally 5 % PUFA. It’s the same composition of fats in our fat body stores of at least 10 kg animal fat. The perfect source of an essential nutrient as animal meat is the perfect source of other essential nutrients.

    Carbohydrates are toxic if more than 7 g in the blood of a 70 kg (=154 lb). More than 30-50 g glucose in the blood is lethal. So why should we eat nonessential and even toxic/lethal carbohydrates?

  5. avatar Dan says:

    I also noticed this story on the BBC and I thought at the time there were so many holes. I didn’t imagine that they could have run so many headlines on the basis of such a tiny correlation coefficent, thanks for pointing that out!

  6. avatar John Walker says:

    Nadine,
    I believe that fat is a substance. (Which it is!) The word ‘fat’ itself is a noun, and not an adjective. Obese is and adjective, to describe someone who carries too much body-fat. Because this distinction is ignored, it’s become an accepted “fact”, that fat makes us ‘fat’!
    As for chocolate being good or bad, surely it’s the same in theory as saying ‘It isn’t the beef-burger that’s the problem; it’s the bun!’ I.e., it isn’t the chocolate that’s the problem, it’s the sugar they put into it! :)

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