The 1 Lifestyle Choice A Longevity Expert Prioritises For A Longer Life
You might have seen recently that Nobel Prize-winning chemist Dr Venkatraman Ramakrishnan and heart surgeon Dr Jeremy London shared their three rules for a longer life: eat well, move enough, and prioritise sleep too.
But speaking to Business Insider, Dr Sofiya Milman, who studies the lifestyles of centenarians for a living, said she thinks one of those lifestyle choices is more important than the others.
'We have people who live to 100 and are healthy, so our bodies are capable. It's biologically plausible, therefore we just have to tweak things to get us there,' she told the publication.
The boring answer is all of them – a combination of 'exercising, eating a healthy diet, reducing stress in my life, and getting enough sleep' is key to the experts' own routine, she said.
But when asked which factor people should prioritise if they had to pick one (and it's important to remember most of us don't have to choose), she went with exercise.
Muscle mass loss, also called sarcopenia, is a normal part of ageing that begins around the age of 30.
But it's associated with a higher risk of falls, increased risk of dementia, and general mortality among older people.
You can fight sarcopenia through resistance and strength training.
It's almost never too late to start – those who picked up their first weight aged 71 saw fantastic results.
But ultimately, she said, the best exercise is the one you'll actually stick with.
In her studies of centenarians, Dr Milman said the things we'd expect to correlate to a longer life don't necessarily always ring true among 'super-agers'.
'They drink the same amount of alcohol, they exercise the same – no less, no more – they're just as likely to be overweight,' she shared.
'And so there isn't a lifestyle feature that we can say, well, if you do that, then you'll live to be a hundred.'
Of course, lifespan is a different thing to healthspan, which is how long you feel well and physically healthy.
So trying to stave off chronic conditions like diabetes, heart disease, and cognitive decline for as long as possible is ideal, she advised.
3 Research-Backed Longevity Rules A Heart Surgeon Swears By
10 Everyday Habits That Are Harming Your Longevity The Most
I'm A Longevity Expert – This 30-Second Test May Reveal Your Risk Of Early Death

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A biotech company sold over 500,000 AI-powered health testing kits. Two C-suite leaders share how they kept science at the center.
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How do your science and tech teams work together to keep the AI models accurate, safe, and compliant? Momo Vuyisich: It's not just collaboration between science and tech — it's a companywide effort. On the science side, we focus on three areas: lab work, data analysis, and clinical research. Whenever we're working on a health product, we rely on clinical research to guide development. This includes observational studies, where we learn from large groups of people, and interventional trials, where we test whether a tool works in real-world settings. For diagnostics, that means formal device trials. In the lab, we use a method called metatranscriptomics, measuring RNA to understand what's happening in the body right now. Unlike DNA, which stays the same, RNA changes based on things like diet or environmental exposure. That allows us to detect early signs of disease like inflammation or even cancer, based on how genes are being expressed. We measure gene activity across human cells, bacteria, and fungi, and we also identify the types of microbes present in a sample. Guru Banavar: What makes our approach powerful is the scale and detail of the data we collect. Each customer sends us stool, blood, and saliva samples, which we use to generate tens of millions of data points showing what's happening in their gut, blood, and mouth. Once that data hits Viome's cloud platform, my team steps in. We use AI to figure out not just what organisms are present, but what they're doing, like whether they're producing anti-inflammatory compounds or if certain biological systems are out of balance. We work with molecular data, which is far more complex than the text data most AI tools are trained on. So we use a range of machine learning methods, such as generative AI and algorithms that learn from labeled examples and draw insights based on patterns, where it's appropriate. 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Second, when applying AI to health products, focus on areas and methods that can be independently validated and, ideally, interpretable, where companies can explain how the AI models reached their results to scientists, clinicians, and users. Finally, it's possible, even in the health domain, to build products with an MVP mindset and implement a process for continuous improvement. Vuyisich: Deeply understand the problem you're trying to solve and identify a robust solution. At Viome, we set out to find the root causes of chronic diseases and cancer, which required measuring tens of thousands of human biomarkers relevant to health. Also, use a method that's accurate, affordable, and scalable. We spent over six years optimizing one lab test — metatranscriptomics — to go beyond the gold standard. This one test gives us thousands of biomarkers across multiple sample types with high accuracy. Finally, it's all about the people. Build a leadership team that deeply understands business and science, is aligned with the mission, and puts the company ahead of personal interests. Hire motivated, self-managed employees, train them well, and continuously coach them. Read the original article on Business Insider

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