Research 101:
Correlation is not causation.
CC
Sure when you factor in the “bacon double cheeseburger super sized with a Diet Coke” phenomenon. I love the taste of diet soda, and it really helps me maintain my weight bc I’m a calorie counter. I rarely drink alcohol, so I basically never need to enter drinks into my food app. It makes life a lot easier.
Ahh, no. Its not 1970 and we arent talking about TAB. This crap is snuck into damned near everything for everyone.
Young people all over are drinking this garbage because their idiot parents told them its safer and will help them avoid diabetes. Little toddlers have no choice and dont know any better but are regularly drinking this stuff because companies we knew (Little Hugs, Tang, etc) as kids have changed the ingredients we had for for a cocktail of manmade garbage that contains two or three of these in the same product.
Ive been watching labels and avoiding this stuff since it came out but most people dont realize where it has been added in products they trusted. That chewing gum youve always used? Yup, its in there now. “Healthy” juices? Yup, full of it. Those fruit cups that are soooo good for your kids? Yup, there too. How about some light yogurt? Whipped sweetener. Speaking of sweetener, that “creamer” so many of you use in your coffee? Many of those are full of it too especially the flavored ones. You should have stuck with that evil racist dairy.
Yes, that is what I was thinking.
Part of it, as you say, is fat people are more likely to drink diet soda. But this study is even weaker. They tried to remove, via statistics, a bunch of factors (what they ate, exercise, BMI, etc) and still came up with an almost invisible effect:
The difference in heart attacks, etc was 346 per 100,000 person years in higher consumers and 314 per 100,000 person years in non-consumers. A difference of just 32 negative events in 100,000 person years! So a thousand people living 100 years would see a difference of just 32 events...
Every time you apply a statistical filter to remove some factor - lack of exercise, for example - you create error. No one KNOWS the exact effect of lack of exercise, so no filter can remove it with perfect accuracy!
And after all the manipulation for a wide variety of factors, they came up with a difference of just 32 negative events in 100,000 person-years!