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Since it's so new, of course there aren't any long-term data on GLP-1 takers. However, relying on prior knowledge about people who are good on the metrics, it c
by samus 1y ago
Since it's so new, of course there aren't any long-term data on GLP-1 takers. However, relying on prior knowledge about people who are good on the metrics, it can be presumed that they will do fine. And won't create financial risk for the insurer due to passing on earlier than expected. But only if they keep taking their meds and/or fix any underlying behavioral and health issues that made them obese in the first case!
Regarding the graph about slippage: yes, that looks like the Covid peak. However, even assuming this recent trend is an anomaly, the industry is in a changing landscape and needs to adapt. New metrics and criteria, and the fastest mover will capture the market. Business as usual.
I don't feel sad except for the people who managed to bring their health issues under control and now can't get life insurance.
- alvah 1y agoGLP-1 isn’t new - the first trials were 20 years ago & there’s a lot of long term data from its use in diabetes management, prior to the weight loss application.
- samus 1y agoOk, sure - but are diabetes patients representative of the whole target market for GLP-1? And there will still be an uncomfortable variable that controls the outcome - patient compliance. That's what makes life insurers woozy.
- oger 1y agoI didn't have look on the studies but I would not be surprised if a decent amount of participants were completely healthy individuals. And maybe (more from random sampling) some unsuspicious mildly overweight without other problems. Especially in the earlier cohorts of testing.
- refulgentis 1y agoRight, you should read it though, we're in the weeds over here, it's not just sort of free-assocating chat, we're picking apart specific things about the article. One of them, as I mentioned 4 up, is that the study with the 65% # is confounded because the groupings involve type 1 diabetes, and also, the number rebounds higher than the # who stopped