Cardiovascular And Metabolic Health

In Okinawa, Japan, the average life expectancy is 84 years. In India, it's 67 years. That’s 17 years of missed birthdays, moments, and memories. Why? The secret isn’t medicine or money. It’s small, daily habits that protect the body and mind over time. ▶︎ 1. They eat until 80% full It’s called ‘Hara Hachi Bu’. No overeating. No “clean your plate” pressure. It gives their metabolism less to process - and reduces inflammation over time. ▶︎ 2. Daily movement is built into life They follow the principle of ‘Karada O Ugokasu’ - “move your body naturally.” Instead of formal exercise, they walk to visit neighbors, and tend gardens every day. The goal isn’t intensity. It’s consistency through natural motion. ▶︎ 3. Plant-heavy, simple meals Okinawans follow the ‘Washoku tradition’ - a traditional Japanese eating style focused on balance, seasonality, and variety. Their plates are small. Their portions are modest. Even chopsticks help - slowing down eating and reducing bite sizes. ▶︎ 4. Strong community ties They have ‘Moai’ - tight-knit social groups that support each other for life. This community helps lower stress, strengthens immunity, and is linked to reduced risk of chronic disease and early death. ▶︎ 5. Purpose beyond work They call it Ikigai - a reason to get up each morning. Whether it’s mentoring younger generations, work, art, or caring for plants - they stay mentally and emotionally engaged well into their 90s. The result? Lower rates of diabetes, heart disease, cancer, and depression - even in their 90s. Remember, none of this requires more money or more effort. Just small shifts in how we live each day. Hit repost 🔁 if this made you rethink your habits. Someone in your connections might need that nudge too. #health #wellness #longevity

A groundbreaking new treatment known as VERVE-102 is poised to revolutionize the way we prevent heart attacks. Unlike traditional cholesterol-lowering medications like statins, which must be taken daily for life, VERVE-102 offers a one-time gene-editing injection that could provide lifelong benefits. The therapy works by targeting and deactivating a specific gene in the liver, PCSK9, which plays a crucial role in regulating levels of low-density lipoprotein (LDL) cholesterol — commonly referred to as "bad" cholesterol. By switching off this gene, the liver becomes more efficient at clearing LDL from the bloodstream, resulting in a sustained 50% reduction in cholesterol levels. This treatment is currently in clinical trials and has already been administered to patients in the UK, including at University College London and Barts Health NHS Trust. According to Prof. Riyaz Patel, an academic cardiologist involved in the trials, the results so far have been “spectacular.” He emphasized that this is not a concept out of science fiction — it is real, in practice, and may fundamentally change the landscape of cardiovascular health management. For patients who struggle with daily medications or who experience side effects from statins, VERVE-102 represents a potential lifesaving alternative that simplifies long-term care. What makes VERVE-102 especially significant is its gene-editing approach, which involves altering a very small section of DNA to suppress PCSK9 production. This strategy not only ensures a permanent effect but also opens doors to similar interventions for other chronic conditions. If approved after further safety and efficacy trials, it could mark a paradigm shift in preventive medicine, reducing the global burden of heart disease, one of the leading causes of death worldwide.

𝐍𝐞𝐰 𝐨𝐛𝐞𝐬𝐢𝐭𝐲 𝐝𝐞𝐟𝐢𝐧𝐢𝐭𝐢𝐨𝐧 𝐬𝐢𝐝𝐞𝐥𝐢𝐧𝐞𝐬 𝐁𝐌𝐈 𝐭𝐨 𝐟𝐨𝐜𝐮𝐬 𝐨𝐧 𝐡𝐞𝐚𝐥𝐭𝐡 𝘍𝘳𝘦𝘴𝘩 𝘢𝘱𝘱𝘳𝘰𝘢𝘤𝘩 𝘵𝘰 𝘥𝘪𝘢𝘨𝘯𝘰𝘴𝘪𝘯𝘨 𝘵𝘩𝘦 𝘤𝘰𝘯𝘥𝘪𝘵𝘪𝘰𝘯 𝘭𝘰𝘰𝘬𝘴 𝘢𝘵 𝘩𝘰𝘸 𝘦𝘹𝘤𝘦𝘴𝘴 𝘣𝘰𝘥𝘺 𝘧𝘢𝘵 𝘢𝘧𝘧𝘦𝘤𝘵𝘴 𝘵𝘩𝘦 𝘣𝘰𝘥𝘺. Exciting developments in the field of obesity research! As you may have noticed in the news yesterday, a group of 58 researchers has proposed a new definition of obesity, published in The Lancet Diabetes & Endocrinology. This updated approach shifts the focus away from BMI and emphasizes how excess body fat (adiposity) impacts organ function and daily activities. The proposed categories—𝐩𝐫𝐞𝐜𝐥𝐢𝐧𝐢𝐜𝐚𝐥 𝐨𝐛𝐞𝐬𝐢𝐭𝐲 (excess fat without organ damage) and 𝐜𝐥𝐢𝐧𝐢𝐜𝐚𝐥 𝐨𝐛𝐞𝐬𝐢𝐭𝐲 (fat causing harm)—aim to better capture the complexity of the condition. I was invited to provide commentary for the 𝘕𝘢𝘵𝘶𝘳𝘦 𝘕𝘦𝘸𝘴 article on this topic. I fully support the new concept that obesity is not a weight problem but a condition of dysfunctional, diseased fat mass. Better diagnostics are needed than simply relying on BMI. And if it were always as simple as solely ‘eat less and move more’ to effectively treat obesity once it is present, we wouldn’t have an obesity epidemic. There is a need for better obesity care and clearer guidance on who should be treated and who can suffice with preventive measures. "This paper excellently highlights the complexity of obesity and the critical role of excess and inflamed fat mass in driving health issues.'' With the new proposal for diagnosis, both overdiagnosis of obesity (e.g., a bodybuilder with a BMI of 32 will no longer qualify as having obesity) and underdiagnosis (e.g., a person with a BMI of 28 but increased waist circumference and high blood pressure will now be diagnosed as having obesity) will be reduced. Measuring fat mass in practice can be challenging and costly, especially when using advanced tools like DEXA scan, as mentioned in the article. Fortunately, simpler measures like waist circumference, when used alongside BMI, are also highlighted as highly valuable. These new concepts align well with the in 2023 updated Dutch obesity guidelines initiated by Partnerschap Overgewicht Nederland (PON) offering a more practical and nuanced approach to diagnosing and managing obesity. Thanks to Giorgia Guglielmi for the interview for this Nature News article 👇 https://lnkd.in/giiTcWA2

𝗔𝗜 𝗖𝗮𝗻 𝗡𝗼𝘄 𝗣𝗿𝗲𝗱𝗶𝗰𝘁 𝗛𝗲𝗮𝗿𝘁 𝗙𝗮𝗶𝗹𝘂𝗿𝗲 𝗙𝗶𝘃𝗲 𝗬𝗲𝗮𝗿𝘀 𝗕𝗲𝗳𝗼𝗿𝗲 𝗜𝘁 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝘀 A fascinating paper published this week in the The American Journal of Cardiology. The important question it asked was the following. Can we predict heart failure before the heart has already begun to fail? The answer, it now appears, is yes. A team led by Prof Charalambos Antoniades MD PhD FRCP FMedSci at the University of Oxford has developed an AI tool that analyses the fat surrounding the heart from routine cardiac CT scans, predicting a patient's risk of developing heart failure up to five years before any clinical signs appear. Epicardial adipose tissue (EAT) is a metabolically active visceral fat depot that is both a sensor and a modulator of myocardial biology and changes its composition in response to paracrine signals from the myocardium. The team hypothesised that radiomic characterization of EAT from routine coronary computed tomographic angiography (CCTA) can noninvasively capture this adverse remodeling and enable early heart failure (HF) risk stratification. The study involved over 72,000 patients across nine NHS centres, followed for up to a decade. The fat around the heart, it turns out, acts as a potential biological sensor. Patients in the highest risk group were twenty times more likely to develop heart failure than those in the lowest. The tool predicted five-year risk with 86% accuracy, outperforming models built on traditional risk factors alone. What is striking is the conceptual shift this represents. We have spent decades in cardiovascular medicine treating disease that has already declared itself, responding to symptoms, managing complications, optimising a heart already under strain. We have been using risk stratification of cardiac disease using various methods like calcium scores. The team are now seeking NHS regulatory approval and adapting the tool for any CT scan of the chest, not just cardiac ones. Every scan, for any reason, could soon carry an embedded layer of cardiac risk intelligence. As the NHS shifts into prevention as part of the long term plan these tools become more important.

Is Body Roundness Index (BRI) the future - or just a companion - to BMI? For decades, Body Mass Index (BMI) - weight ÷ height² - has been the standard gauge of healthy weight. But its limitations are well‑documented: it ignores fat distribution, muscle vs. fat mass, sex, age and ethnicity. A muscular athlete (or Olympic-level rugby star) can end up labeled “overweight” by BMI even if they’re metabolically healthy. Enter: the Body Roundness Index (BRI) Developed in 2013, BRI uses waist circumference and height - modeled geometrically using body shape eccentricity - to estimate total and visceral body fat, not just size. Values typically range from 1 to 16, with higher scores indicating a “rounder,” more centrally obese figure. What scientific data suggests: A major study of ~10,000 Chinese adults showed that those with high stable BRI over six years had a 163% higher risk of cardiovascular disease compared to a low-BRI group; mid-range BRI saw a 61% higher risk. This held even after adjusting for age, smoking, cholesterol, etc. In US data from nearly 33,000 adults (from 1999–2018), both very low (<3.4) and high (>6.9) BRI scores were linked to increased all-cause mortality - up to 49% higher risk at the upper extreme compared to the mid-range. The pros of using BRI: Reflects abdominal (visceral) fat, a key driver of metabolic disease risk, something BMI doesn’t capture. Avoids misclassifying highly muscular individuals or those with different body compositions. Shown to correlate with multiple outcomes - heart disease, all-cause and metabolic mortality, fatty liver, hypertension, bone mineral issues - often outperforming BMI alone. Limitations and context: Calculation is more complex, it requires waist measurement and a formula using eccentricity; less convenient than BMI. Accuracy may vary by ethnicity, sex, age; most validation studies have focused on East Asian or US populations. Measuring waist circumference consistently is error‑prone in clinical or home settings. BMI has broad longitudinal datasets, clear thresholds, and institutional support; BRI is promising, but still early in adoption. So … is BRI the new BMI? Not quite, but it’s a compelling complement or upgrade, especially when fat distribution matters. BRI offers a deeper view into shape and risk by focusing on visceral fat. What we should take away: BMI remains a useful starting point but does not tell the full story. BRI adds value, particularly in cardiovascular and metabolic risk screening. In practice, a combination of metrics (e.g. BMI + WHtR + BRI), plus clinical biomarkers, offers the best health assessment. In summary: BRI isn’t replacing BMI overnight. But it advances our understanding of the most important risk driver: where fat is stored, not just how much. For professionals and health‑savvy professionals evaluating risk in diverse populations, it’s a tool worth knowing and potentially using.

🌍✨ Rethinking Obesity: A Landmark Redefinition with Major Implications ✨🌍 Obesity has long been one of the world’s most pressing health challenges — but new evidence suggests the problem is even bigger than we thought. 📊 Under the new 2025 Lancet Commission definition:    •   69% of adults met criteria for obesity — vs 43% under the traditional BMI ≥ 30 kg/m²    •   The new definition moves beyond BMI, focusing on organ and tissue dysfunction caused by excess adiposity — shifting the lens from weight to health impact 💥 Clinical obesity was associated with: • 6× greater risk of diabetes • 6× higher risk of cardiovascular events • 2.7× increased risk of all-cause mortality 🌏 Who’s most affected? • Asian individuals saw the largest relative increase — up 90%, from 27% → 51% under the new criteria • Prevalence rises with age — 44% of those 18–29 vs 78% of those 70+ 💡 Why this matters: This is more than a reclassification — it’s a paradigm shift. By defining obesity as a chronic, systemic illness, the Commission calls for a move away from BMI as the main health measure and toward a framework that truly reflects biology, risk, and impact. The findings — drawn from the NIH’s groundbreaking All of Us program — reveal that we may be underestimating both the scale and the stakes of obesity. 📖 Read the full JAMA Network Open study here: 👉 https://lnkd.in/eZb8iAwQ 💭 A powerful reminder: measuring health by weight alone misses the true picture — redefining obesity is essential to tackling its global burden. #obesity #publicHealth

New research in JACC: Advances shows that the eye may offer a powerful, noninvasive window into coronary artery disease detection. In a multicenter study of 383 patients, deep learning models trained on retinal images were able to identify CAD with strong performance, outperforming traditional clinical risk scores, particularly in intermediate risk patients where clinical uncertainty is highest. When retinal imaging was combined with clinical indicators using a multimodal AI approach, diagnostic accuracy improved further, achieving an AUC of 0.91 with over 92 percent sensitivity. Because retinal and coronary vessels share similar vascular origins, microvascular changes captured by OCT and OCTA appear to reflect underlying coronary disease. AI enables these subtle patterns to be translated into scalable, radiation free screening and risk stratification tools. This work points toward a future where cardiovascular risk can be assessed earlier, more safely, and more equitably, especially in settings where invasive testing is limited. Multimodal AI may be key to shifting CAD detection upstream and personalizing prevention before clinical events occur. 🔗 https://lnkd.in/gWJUU447 Follow Zain Khalpey, MD, PhD, FACS for more on Ai & Healthcare. #AIinHealthcare #Cardiology #CoronaryArteryDisease #PreventiveCardiology #DigitalHealth #MedicalAI #MultimodalAI #DeepLearning #NonInvasiveDiagnostics #RetinalImaging #OCTA #OCT #CardiovascularHealth #RiskStratification #PrecisionMedicine #ClinicalInnovation #HealthEquity #CVImaging

Why meal timing is a hormonal decision, not a lifestyle preference As RDs, we often focus on what our clients eat. But physiology keeps reminding us that when they eat they may be just as powerful. Our bodies run on a 𝗰𝗶𝗿𝗰𝗮𝗱𝗶𝗮𝗻 𝗿𝗵𝘆𝘁𝗵𝗺 (a 24-hour biological clock) that tightly regulates hormones, metabolism, appetite, and glucose control. This image tells a very important story. The circadian rhythm controls hormones across the day 𝗠𝗼𝗿𝗻𝗶𝗻𝗴 (around 6:00 AM) 🌅 ▪️Cortisol rises = promotes alertness and glucose availability ▪️Testosterone (in men) peaks = anabolic readiness Metabolic efficiency is higher ➡️ The body is primed to eat, absorb, and use nutrients 𝗠𝗶𝗱𝗱𝗮𝘆 (around 12:00 PM) ☀️ ▪️Adiponectin activity supports insulin sensitivity ▪️Glucose handling is still efficient ➡️ This is why larger meals earlier in the day are often better tolerated 𝗘𝘃𝗲𝗻𝗶𝗻𝗴 (around 6:00 PM) 🌆 ▪️Insulin sensitivity declines ▪️Glucose clearance slows ➡️ The same meal now produces a higher glucose and insulin response 𝗡𝗶𝗴𝗵𝘁 (around 12:00 AM) 🌙 ▪️Melatonin & growth hormone rise ▪️Leptin signaling shifts ▪️TSH, prolactin, vasopressin follow nocturnal rhythms ➡️ The body shifts into repair and recovery, not digestion Late eating at this stage sends #conflicting signals to metabolism. So, What happens when timing is ignored? • Higher fasting glucose • Increased insulin resistance • Poor appetite regulation • Weight gain despite (correct) calories • Sleep disturbance This is circadian misalignment Not lack of willpower. For this reason, we ask clients about when they eat ⏳ Because: ▪️Hormones follow time, not calories ▪️The same diet can produce different outcomes depending on timing ▪️Meal timing is a clinical lever, not a trend 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗮𝗹 𝘁𝗮𝗸𝗲𝗮𝘄𝗮𝘆𝘀 for clinical practice • Encourage earlier energy intake • Reduce late-night meals and snacking • Anchor meals to consistent daily times • Align nutrition with sleep-wake cycles 👇🏻👇🏻 Think #hormones first, #calories second ☝🏻☝🏻 Always remember: Nutrition isn't happening in isolation. It happens inside a time-regulated hormonal system. And as RDs, respecting that clock can dramatically improve outcomes. #Nutrition #Healthcare #Education #health #HealthyLiving #mentalhealth #LinkedIn #nutritionist #diet #food #dietitian

How your gut microbes help set your body’s internal clock This figure shows how the gut and brain communicate through neural, immune, endocrine, and metabolic pathways that are influenced by the body’s internal clock. The microbiome, hormones, and light–dark cycles interact to coordinate sleep, metabolism, stress responses, and inflammation across the gut–brain axis. 1️⃣ Central and peripheral clocks The brain’s master clock in the suprachiasmatic nucleus (SCN) aligns daily rhythms with environmental light through the retinohypothalamic tract. Peripheral clocks, including those in the gut, follow signals from the SCN but also respond to feeding times and microbial metabolites. 🟢 Example: Disrupted light exposure or irregular eating can desynchronize the gut’s circadian rhythm, altering microbial composition and metabolic regulation. 2️⃣ Endocrine pathway The hypothalamic–pituitary–adrenal (HPA) axis links stress and circadian timing through hormone signaling. Gut microbes influence HPA activation by releasing metabolites and cytokines that affect cortisol release. 🟢 Example: Certain bacteria such as Actinobacteria and Streptococcus modulate HPA activity, contributing to changes in inflammation and stress hormone output. 3️⃣ Immune pathway Microbial components interact with immune cells in the intestinal mucosa, producing cytokines that reach the brain through circulation or vagal signaling. 🟢 Example: Lipopolysaccharides (LPS) and pattern-associated molecules from gut bacteria trigger IL-1β and TNF-α release, linking dysbiosis to neuroinflammation and altered sleep quality. 4️⃣ Metabolic pathway Microbes regulate lipid and glucose metabolism through production of short-chain fatty acids and other metabolites that follow circadian patterns. 🟢 Example: Species like Lactococcus chungangensis and Ruminococcus bromii affect lipid metabolism, aligning energy use with the body’s day–night cycle. 5️⃣ Neural pathway The vagus nerve transmits microbial and immune signals bidirectionally between gut and brain. Neurotransmitters and microbial by-products influence mood, stress, and cognition through this circuit. 🟢 Example: Cytokines and bacterial metabolites act on vagal afferents, shaping neural activity in regions that regulate alertness and emotional balance. Together, these pathways demonstrate how the microbiome acts as a peripheral clock that integrates environmental cues, diet, and stress signals with the brain’s circadian system. When alignment breaks down, it contributes to insomnia, metabolic dysfunction, and inflammation across multiple organ systems. https://lnkd.in/g3U47VEN

Insulin resistance isn't one disease. It's an accumulated signal loss. Most people blame sugar.  That's part of the story. But after 30 years in medicine, I've learned something more important: Small biological signals create big metabolic shifts. Your cells have insulin receptors. When insulin binds, glucose moves from the blood into the cell. When those receptors are overstimulated, under-recovered, inflamed, or chronically disrupted, they become less responsive. Glucose lingers.  Insulin rises.  Compensation begins. Over the years, it becomes: ↳ Type 2 diabetes  ↳ Fatty liver  ↳ Heart disease  ↳ Cognitive decline Decades of silent adaptation before a single symptom appears. Most treatment focuses on diet alone. The biology tells a bigger story. 𝗧𝗛𝗘 𝗦.𝗜.𝗚.𝗡.𝗔.𝗟 𝗙𝗥𝗔𝗠𝗘𝗪𝗢𝗥𝗞 You don't need to restore everything at once.  You restore signals. 𝗦 — 𝗦𝗨𝗡𝗟𝗜𝗚𝗛𝗧  ↳ 10 minutes outside in the morning anchors circadian rhythm and metabolic timing for the entire day 𝗜 — 𝗜𝗡𝗧𝗘𝗥𝗩𝗔𝗟𝗦 𝗼𝗳 𝗴𝗲𝗻𝘂𝗶𝗻𝗲 𝗵𝘂𝗻𝗴𝗲𝗿  ↳ A 12-hour overnight fast supports receptor resensitisation and cellular repair 𝗚 — 𝗚𝗟𝗨𝗖𝗢𝗦𝗘 𝗱𝗶𝘀𝗽𝗼𝘀𝗮𝗹 𝘁𝗵𝗿𝗼𝘂𝗴𝗵 𝗺𝗼𝘃𝗲𝗺𝗲𝗻𝘁  ↳ A 10-minute walk after meals activates non-insulin-mediated glucose uptake via skeletal muscle 𝗡 — 𝗡𝗜𝗚𝗛𝗧 𝗿𝗲𝘀𝘁𝗼𝗿𝗮𝘁𝗶𝗼𝗻  ↳ Dim light. Consistent sleep timing. Melatonin directly influences insulin signalling 𝗔 — 𝗔𝗖𝗧𝗜𝗩𝗘 𝘀𝘁𝗿𝗲𝘀𝘀 𝗿𝗲𝗰𝗼𝘃𝗲𝗿𝘆  ↳ Cortisol must return to baseline daily. Chronic elevation drives hepatic glucose output and resistance 𝗟 — 𝗟𝗜𝗩𝗜𝗡𝗚 𝗳𝗼𝗼𝗱 𝗱𝗶𝘃𝗲𝗿𝘀𝗶𝘁𝘆  ↳ 30+ plant sources per week support a microbiome that modulates inflammation and insulin sensitivity These changes won't replace medication where it's needed. But they address something medication cannot: The environmental signals that shaped the problem in the first place. You are not insulin-resistant because you lack discipline. You are insulin-resistant because modern life removed signals your biology depends on. Restore the signals.  And the biology responds. Same body.  Different inputs.  Different outcome. 365 days of signal loss compound toward disease. 365 days of signal restoration compound toward decades of health you didn't think were still available. Metabolic disease compounds quietly.  So does metabolic repair. 💾 Save this. Revisit it when you're ready to rebuild the signals. ➕ Follow Dr Tim Patel for medicine explained in ways you can actually use.