Consuming fruits, vegetables, legumes, nuts, fish and whole-fat dairy products is key to lowering the risk of cardiovascular disease, including heart attacks and strokes. The study also found that a healthy diet can be achieved in various ways, such as including moderate amounts of whole grains or unprocessed meats.

The World Health Organization estimates ~18 million people died from cardiovascular disease in 2019, representing 32% of all global deaths. Of these deaths, 85% were due to heart attacks and strokes. Population Research Health Institute researchers and their global collaborators analyzed data from 245,000 people in 80 countries from multiple studies.

  • stravanasu
    link
    fedilink
    English
    5
    edit-2
    1 year ago

    P-values-based methods and statistical significance are flawed: even when used correctly (e.g.: stopping rule decided beforehand, various “corrections” of all kinds for number of datapoints, non-gaussianity, and so on), one can get results that are “statistically non-significant” but clearly significant in all common-sense meanings of this word; and vice-versa. There’s a constant literature – with mathematical and logical proofs – dating back from the 1940s pointing out the in-principle flaws of “statistical significance” and null-hypothesis testing. The editorial from the American Statistical Association gives an extensive list.

    I’d like to add: I’m saying this not because I read it somewhere (I don’t like unscientific “my football team is better than yours”-like discussions), but because I personally sat down and patiently went through the proofs and counterexamples, and the (almost non-existing) counter-proofs. That’s what made me change methodology. This is something that many researchers using “statistical significance” have not done.

    • @[email protected]
      link
      fedilink
      English
      5
      edit-2
      1 year ago

      This is interesting and something I’ve not heard of - can you recommend a starter link for someone with a basic stats background? I had some in undergrad, but this sounds like a topic that could get very tinfoil-hat-y if not searched correctly and with good context.

      • stravanasu
        link
        fedilink
        English
        8
        edit-2
        1 year ago

        There’s still a lot of debate around this topic. It’s obviously difficult for people who have used these methods for the past 60 years to simply say “I’ve been using a flawed method for 60 years” – although in the end that’s how science works. The problem moreover is double: the method has built-in flaws, and on top of that it’s often misused.

        Some starters:

        What’s sad is that these discussions easily end in political or “football-team”-like debates. But the mathematical and logical proofs are there, for those who care to go and read them.

    • @vin
      link
      English
      11 year ago

      Ah, I thought you were talking about p-values - which is just a simple metric and gets a bad rep from being used for statistical significance. Statistical significance certainly is trash.

      • stravanasu
        link
        fedilink
        English
        11 year ago

        Yes I’m talking about p-values. Statistical “significance” is based on p-values.