In 2003, two doctors stood next to each other for a DEXA scan. One was Chittaranjan Yajnik, an Indian endocrinologist. The other was John Yudkin, a British physician. They had identical BMIs of 22.3. By every screening number a doctor would normally use, they were the same body.

Yajnik’s body fat was 21.2%. Yudkin’s was 9.1%.

They published a single page in The Lancet and called it the YY Paradox (Lancet, 2004). The point was small and devastating. Same weight, same height, same BMI. Two completely different bodies. The fat that drives heart attacks and diabetes was sitting where the scale and the tape measure couldn’t see it. (Twice the body fat at the same weight. The scale couldn’t tell you which body was which.)

The lesson is bigger than DEXA. Weight is one number, and possibly the least interesting one on your body. The four numbers that predict how you’ll age are hidden underneath it.

TL;DR

• Your weight is the sum of four things that age you very differently: fat mass, lean mass, visceral fat, and bone density. Each is independently predictive.

• Lean mass predicts falls, frailty, and all-cause mortality after 60.

• Visceral fat drives heart disease, diabetes, and fatty liver.

• Body fat percentage catches the “thin outside, fat inside” trap.

• Bone density triggers the only hard clinical decision in the set: treat for osteoporosis or not.

• South Asians carry more body fat and less limb muscle at the same BMI than every other ethnic group studied. The scale is more misleading for us, not less.

• The gold-standard tool that reads all four in one ten-minute scan: DEXA. $150-300, radiation about a day of background.

Weight is one metric. These four matter more.

Body weight is a sum. It is the only health number most people track because it is the only one a bathroom scale can produce. But the same 180 lbs can be a lean, strong body composition with low visceral fat, or a sarcopenic body with a fatty liver and an elevated fracture risk. The scale cannot tell you which one you have.

The four numbers it hides (fat mass, lean mass, visceral fat, and bone density) each track a different way the body fails over time. Each moves in response to different inputs. Each matters at a different age. Tracking your weight without knowing what’s underneath it is like tracking your portfolio’s total dollar value without knowing what’s in it. The number tells you what you have. It does not tell you what is working.

Lean mass is the strongest mortality signal in older adults. A meta-analysis of prospective cohort studies found that adults over 65 with low skeletal muscle mass had a 56% higher risk of all-cause mortality than those with normal muscle (PLOS One, 2023; systematic review and meta-analysis). The functional version is what most people feel before any lab confirms it: less strength, slower stairs, more falls, longer recovery from anything that puts you in a hospital bed. South Asians start with less to spare. Compared with European men of similar weight, height, and age, Asian Indians have significantly less skeletal muscle in their limbs along with more central fat (British Journal of Nutrition, 2009). What moves it: protein at 0.75 to 1g per pound of lean body mass, two to three resistance training sessions a week, enough sleep to recover, and optimized hormones. After 40, you are either building lean mass or losing it. There is no holding it steady by accident.

If you’re on a GLP-1, this matters more, not less.
In the SURMOUNT-1 DXA substudy, about 25% of every pound lost on tirzepatide (Mounjaro, Zepbound) was lean tissue (Diabetes, Obesity & Metabolism, 2025; n=160). A real-world analysis of nearly 8,000 patients found tirzepatide drove greater lean mass loss than semaglutide (Ozempic, Wegovy) in routine care (medRxiv, 2026; n=7,965). Without a DEXA, the scale tells you the drug is working. The DEXA tells you whether your protein and training are keeping the right tissue.

Visceral fat, the deep abdominal fat that wraps your liver and pancreas, drives heart attacks, type 2 diabetes, and fatty liver progression independent of BMI or total body fat. On your DEXA report it shows up in pounds or square centimeters; above 100 cm² (or about 2 lbs) is the threshold most clinicians flag as elevated cardiometabolic risk (Hologic DXA reference; Nicklas et al., Obesity Research, 2004). What moves it: cut refined carbs and ultra-processed food, add fiber and lean protein, layer in Zone 2 cardio two to three times a week, and fix sleep. We’ll cover the drivers and treatments as their own topic in the next issue.

Body fat percentage catches the “thin outside, fat inside” pattern the YY Paradox first showed. In a recent NHANES analysis of US adults aged 20 to 49, body fat above 27% in men or 44% in women carried a 78% higher all-cause mortality risk over 15 years and more than three times the risk of heart disease mortality, while BMI lost statistical significance after adjustment (Annals of Family Medicine, 2025). The BMI says you are fine. The body fat number says whether that is true. Healthy ranges run roughly 10-20% for men and 20-30% for women, though the right target depends on age and goals. What moves it: a sustained caloric deficit if you are cutting, paired with the resistance training that keeps lean mass on. The same sleep and stress hygiene that moves every other metric on this list. There is no shortcut that doesn’t show up as muscle loss on the next scan.

Bone mineral density is the only DEXA number that drives a hard clinical decision: whether to treat for osteoporosis. Roughly 1 in 3 women and 1 in 5 men over age 50 will experience an osteoporotic fracture in their remaining lifetime (International Osteoporosis Foundation; Kanis et al., Osteoporos Int, 2000). The T-score on your report tells you where you stand. Above -1 is normal. Between -1 and -2.5 is osteopenia. Below -2.5 is osteoporosis. South Asian women have lower bone mineral density on standard DEXA scans, and the T-score reference data was built on Caucasian populations. A “normal” T-score can still underestimate fracture risk for South Asian women (Zengin et al., Frontiers in Endocrinology, 2015; review). What moves it: adequate calcium, magnesium, and vitamin D; weight-bearing and resistance training; no smoking and alcohol kept low. Hormone therapy is FDA-approved for prevention of bone loss, and for women within 10 years of menopause and under 60, the Menopause Society endorses it for bone protection, not just symptoms (NAMS, Menopause, 2022).

DEXA: The gold standard for measurement

There are other options. Bathroom scales with bioelectrical impedance (BIA) are convenient and cheap, but their fat-percentage readings drift several points with hydration and time of day. Skinfold calipers depend entirely on the technician. The Bod Pod (air displacement) is accurate but rare and pricey. MRI is the most accurate way to measure visceral fat and ectopic fat inside the liver, but it runs $1,500 or more per scan and isn’t ordered for routine body composition tracking.

A DEXA scan shines two low-energy X-ray beams through your body. Bone, muscle, and fat absorb them differently, and the machine reconstructs how much of each you carry, and where. Ten minutes on a table. $150-300 in most US cities. For body composition tracking, it is the most practical tool we have. DEXA-measured visceral fat correlates with MRI at r=0.88 to 0.94 across validation studies (Obesity, 2022). MRI is more accurate at the extremes; for everyday tracking, it is overkill at ten times the price.

DEXA has real limits. It tends to overestimate visceral fat at very high volumes (above ~600 cm³) compared with MRI (Obesity, 2022), and different machines disagree by 1-2%, so the trend on the same machine matters more than any single absolute number. It also doesn’t see ectopic fat inside the liver, pancreas, or heart muscle, which is what an MRI-PDFF or cardiac MRI is for. The least significant change for visceral fat on a GE CoreScan is about 130 grams (Obesity, 2019). Anything smaller than that is measurement noise. Chase trends across two or three scans, not single readings.

What about radiation?

A whole-body DEXA delivers about 2-10 microsieverts (µSv) per scan, depending on the machine. Most centers come in around 5 µSv (COMARE 18th Report, UK Department of Health, 2019; review of DXA dose data). That is roughly one day of natural background radiation in the US, where the average person absorbs about 3,000 µSv per year from soil, cosmic rays, and radon at home.

Exposure Effective dose Whole-body DEXA ~5 µSv Transcontinental flight (NY to LA) 30-40 µSv Chest X-ray 100 µSv Mammogram 280-400 µSv Cardiac CT (calcium scoring) 1,700-3,000 µSv Abdominal CT 8,000-10,000 µSv US background, full year 3,000 µSv

A DEXA is roughly 20 times lower than a chest X-ray and 1,000 times lower than an abdominal CT. The COMARE review estimated that a single DXA scan raises lifetime cancer risk by less than 1 in 1,000,000. Annual scans for body composition tracking, even sustained over decades, sit well inside the 20,000 µSv/year diagnostic exposure limit clinicians use as a guardrail. Pregnancy is the only common reason to defer.

How I use DEXA

I get a baseline DEXA every year. If I’m running a serious cut, a bulk, or starting a new medication that affects body composition, I add scans at the start and end of that window. The baseline is what makes the after number meaningful. Same scanning center every time. Machine-to-machine drift of 1-2% can swamp the real signal.

The first line I check on a new scan is lean mass. If lean dropped faster than fat in proportion, something in the plan is wrong. Protein is too low, the training stimulus isn’t enough, sleep is off, or the intervention is moving the wrong tissue. The report is most useful as an early warning, not a victory lap.

The clearest example I have is a six-month body recomposition window when I was using Tirzepatide. Between July 2024 and January 2025, I went from 244 to 226.5 lbs. The bathroom scale showed minus 17.5 pounds. The DEXA showed something different: fat down from 95 lbs to 69.5 lbs and lean mass up from 141 lbs to 149.8 lbs. Visceral fat down from 5.5 lbs to 3.89. Without the DEXA, the scale would have represented the change inaccurately. I have also had the opposite outcome, where I lost more lean mass than fat. DEXA caught it at the next scan, and I changed the plan before the next cycle.

Myth: “If the scale is going down, I am succeeding.”

The Myth: Weight loss is the goal. If the number on the scale is moving in the right direction, the plan is working.

The Evidence: Body weight is a sum. It hides what changed. In the SURMOUNT-1 DXA substudy of adults on tirzepatide, 25% of every pound lost was lean tissue (Diabetes, Obesity & Metabolism, 2025; n=160). The real-world digital phenotyping study found tirzepatide patients lost more lean mass than semaglutide patients, and the patients who lost the most lean mass also reported the most fatigue and reduced exercise tolerance (medRxiv, 2026; n=7,965). A separate review of older adults losing weight without structured strength training documented similar proportional muscle loss across multiple interventions (Mayo Clinic Proceedings, 2019; meta-analysis). The same 15 pounds on the scale can be a healthy recomposition, a clean fat loss, or a quiet muscle loss the reader will feel five years from now.

The Verdict: The weighing scale measures gravity. The DEXA measures what changed in the body. Especially after 40, and especially as a South Asian starting with less muscle to spare, the detailed numbers matter a lot.

Disclaimer: The information provided in this article is for educational and informational purposes only. It is not intended as a substitute for professional medical advice, diagnosis, or treatment. Always seek the advice of your physician or other qualified healthcare providers with any questions you may have regarding a medical condition or wellness program. Reliance on any information provided in this article is solely at your own risk. The author and publisher of this article make no representations or warranties, express or implied, regarding the completeness, accuracy, reliability, suitability, or effectiveness of the information contained herein. The inclusion of specific products, services, or strategies in this article does not imply endorsement or recommendation. The author and publisher disclaim any liability for any adverse effects or consequences resulting from the use or application of the information presented. You are encouraged to consult with a qualified healthcare professional before making any changes to your diet, exercise routine, or lifestyle.

4-6 weeks in, the CGM wasn’t telling me anything new. I developed a sense of how my body responded to every food I regularly eat. I kept wearing it past the 4-6 week, and it unexpectedly became an accountability tool.

TL;DR

• The first 4-6 weeks of CGM data is genuinely revelatory. Individual glycemic responses vary by 5x for identical foods, and population nutrition charts can’t predict yours

• After that window, the new-data well runs dry. You’ve mapped your staples and the CGM stops surprising you

• The medical critics are right that CGM data is not a substitute for HbA1c in non-diabetics

• Beyond the learning window, the CGM is useful for two things: behavioral accountability (the Hawthorne effect) and early warning on metabolic shifts or drug/supplement side effects

Month one: your personal nutrition map

The first month is where the value lives. The Stanford “glucotypes” study put CGMs on 57 mostly healthy people and found 80% spiked to prediabetic or diabetic glucose levels after eating cornflakes with milk (PLOS Biology, 2018; observational, n=57). The lead researcher’s takeaway: “There are lots of folks running around with their glucose levels spiking, and they don’t even know it.”

The Weizmann Institute tracked 800 participants wearing CGMs for a week, measuring 46,898 meals, and found 5x variation in glycemic response to identical foods between individuals (Zeevi et al., Cell, 2015; observational cohort, n=800). A 2025 study confirmed it: each person has a carbohydrate “fingerprint,” and rice-spikers are more likely to be Asian, which, given my own CGM history, was not exactly a surprise (Wu et al., Nature Medicine, 2025; crossover, n=55).

That variance is the whole reason population nutrition charts fail you. A “low-GI” food is an average across hundreds of people. You might respond very differently to the same food compared to your friend.

So what do you do? Here’s how to spend four weeks with the device.

Week 1: log meals and watch the spikes. What you eat, when you eat it, what happens to your glucose. The spikes you see in your usual pattern are your baseline.

Weeks 2-4: experiment. Some worth testing:

• Eating vegetables and protein first, vs starting with rice or roti

• Building out the plate (more fiber, vegetables, healthy fats, protein), vs starchy carbs alone

• Different starch sources (rice, roti, oats, potato) to see which one spikes you most

• A 15-20 min walk after a meal, vs sitting on the couch

• 10 squats every hour during a long sitting day, vs sitting straight through

• If you are tracking your sleep, see how a good night’s sleep impacts the next day

• A teaspoon of psyllium husk (Isabgol) 30 minutes before the meal

You’ll see which foods consistently spike you, which conditions blunt the spike or cause it to come down quickly, and which interventions actually moved the needle. That’s your personal guide.

After month one: the diagnostic limits

The educational value has a natural end. Once you’ve cycled through your regular foods, the spikes stop being news. You learn how you respond to dal-chawal, your usual breakfast, your post-workout snack. After that, the CGM is showing you variations on patterns you already know.

This is also where the medical critics are right. A 2025 Mass General Brigham study of 972 adults found that CGM metrics correlated well with HbA1c in people with type 2 diabetes, weakly in prediabetes, and showed essentially no correlation in people with normal blood sugar (Diabetes Technology and Therapeutics, 2025; observational). University of Bath researchers found CGMs overestimated “time above range” by nearly 400% compared to gold-standard finger-prick tests in healthy adults, and misclassified low-GI fruits as medium or high-GI (American Journal of Clinical Nutrition, Feb 2025). The lead author explained the gap simply: CGMs measure glucose in the interstitial fluid around your cells, not in your blood, which introduces lag and inaccuracy at the edges.

The critics are evaluating the CGM as a diagnostic tool. As a diagnostic tool for healthy adults, it doesn’t really work, and the error rate is part of why. CGMs are accurate enough for someone whose glucose swings from 80 to 250, because the device’s error band is small relative to the signal. In a healthy adult whose glucose lives between 80 and 140, that same error band is large enough to make a normal post-meal reading look like a spike, or vice versa. The 400% overestimate is what happens when you push an interstitial-fluid sensor into a range it wasn’t optimized for. For most people, the natural endpoint is somewhere around four to six weeks. They’ve learned what they came to learn, and the device has nothing new to add.

Keep it on for accountability

For some people, including me, there’s a second reason to keep wearing it. It’s the Hawthorne effect: when people know they’re being observed, their behavior shifts toward what they think they should be doing. The data doesn’t have to be new for the device to keep working on you.

When my CGM is on, I eat fewer carbs at night, I snack less, I make better choices because I know the data is there, recording everything. When I take it off, I drift. I’ve tested this multiple times over five years. The pattern is consistent. I hate seeing big spikes on the graph, which makes me eat differently.

The same dynamic shows up in daily weighing. A study of 9,768 smart scale users found that only daily weighing was associated with weight loss across all BMI groups (JMIR, 2021; observational cohort, n=9,768). When participants stopped weighing for 30 or more days, they gained an average of 0.85 kg. The mechanism is identical: awareness triggers self-evaluation, which triggers corrective action.

If that kind of accountability is helpful for you, the CGM can be a very useful tool for blood sugar control. If it isn’t, or if it nudges you toward food anxiety instead of better choices, it’s the wrong tool.

Keep it on for early warning

There’s a third reason some people keep wearing one. When I started rosuvastatin (Crestor), I noticed within two weeks that my glucose spikes were getting larger and taking longer to come back down. Statins are known to increase insulin resistance by approximately 24%, with the pancreas trying to compensate until the system tips toward type 2 diabetes (ATVB, 2021). But HbA1c takes two to three months to reflect those changes. My CGM showed the shift in 14 days. I caught a real drug side effect months before my next blood draw would have flagged it.

Separately, I was waking up at 5am every morning for weeks without understanding why. When I looked at my overnight glucose traces, the pattern was obvious. My glucose was dipping in the early morning hours, triggering a cortisol and adrenaline response that pulled me awake (peak window for nocturnal hypoglycemia is between 04:00 and 07:30). I started having a piece of fruit with cottage cheese about an hour before bed, and the early wake-ups stopped within days.

Neither of those would have shown up on a standard lab panel. Postprandial glucose abnormalities can appear years before fasting glucose and HbA1c start to drift, and CGM is the practical way to see them (Journal of Multidisciplinary Healthcare, 2024; review). For South Asians, who develop metabolic dysfunction at lower thresholds, catching these shifts early may matter even more. A 2025 study found CGM metrics could differentiate prediabetes from normoglycemia in Asian individuals even when fasting glucose appeared normal (Chandran et al., Journal of Diabetes Science and Technology, 2025; observational).

Myth: “If you don’t have diabetes, a CGM is a waste of money”

The Myth: CGMs are medical devices for managing diabetes. If your blood sugar is normal, wearing one is expensive wellness theater, paying $100 a month to watch numbers that don’t mean anything clinically.

The Evidence: The belief persists because CGMs were marketed as optimization tools by wellness companies, and endocrinologists rightly pushed back on that framing. The critics are right about the diagnostic claim. But they’re evaluating only one of the device’s possible uses. The first four to six weeks of CGM data are genuinely educational for most people, regardless of diabetes status, because individual glycemic variability is large enough that you cannot predict your response to a food from population averages. After the learning window, the CGM becomes optional. For some people, behavioral accountability (the same psychology that makes daily weigh-ins work for weight loss) makes the cost worth it. For others, early detection of drug side effects or metabolic shifts justifies keeping it on. Most people probably should wear one for a month, learn what they came to learn, and take it off.

The Verdict: The first four weeks are worth it for almost anyone. After that, only if the accountability or early warning value is something you specifically need.

The CGM is a small example of a bigger pattern. Personal data lets you stop arguing with averages. Once you know how your body responds, you stop needing somebody else’s chart. The first month of wearing one is the lesson. What you do after is yours to decide.

How to Try One

You don’t need a prescription anymore. Dexcom Stelo (~$99/month for two 15-day sensors) and Abbott Lingo (~$49 for two weeks, $89 for four) are both OTC and ship directly from the company. Pick one, wear it for a month, run your food experiments. If you’re already on medications that affect glucose (statins, steroids, beta-blockers) or you have a family history of diabetes, loop your doctor in so the data lives in your file. Otherwise, the barrier to entry is lower than it’s ever been. OTC CGMs are slightly less accurate than prescription versions, but unless you have a metabolic diagnosis or risk flag, most doctors won’t prescribe one and insurance won’t cover it. For a one-month learning experiment, OTC is the path.

Disclaimer: The information provided in this article is for educational and informational purposes only. It is not intended as a substitute for professional medical advice, diagnosis, or treatment. Always seek the advice of your physician or other qualified healthcare providers with any questions you may have regarding a medical condition or wellness program. Reliance on any information provided in this article is solely at your own risk. The author and publisher of this article make no representations or warranties, express or implied, regarding the completeness, accuracy, reliability, suitability, or effectiveness of the information contained herein. The inclusion of specific products, services, or strategies in this article does not imply endorsement or recommendation. The author and publisher disclaim any liability for any adverse effects or consequences resulting from the use or application of the information presented. You are encouraged to consult with a qualified healthcare professional before making any changes to your diet, exercise routine, or lifestyle.

Every South Asian family has some version of this argument. The aunties swear by ghee (loudly). The cardiologists say cut it. The internet is split between “ancestral superfood” and “arterial poison.”

I am a Punjabi and grew up in Delhi, with ghee in our kitchen. In the parathas, on the dal, stirred into the rice. It was love on the plate. So when I started looking at the evidence, I wanted a real answer.

The largest meta-analysis ever done on ghee and heart disease screened 919 articles and pulled 18 studies covering nearly 20,000 people, roughly 4,500 of them from the Indian subcontinent (Progress in Nutrition, 2025; systematic review and meta-analysis, n=19,948). The result was wide enough to mean “slightly protective” or “slightly harmful” or anything in between.

After all that data, the most honest thing science can say is: it depends. And that “it depends” pointed me somewhere useful.

TL;DR

• Whether ghee raises your numbers depends on your phenotype, your plate, and your labs, not on population averages.

• The 2025 meta-analysis (n=19,948) found no significant heart disease risk from ghee on average. Averages mask wide individual variance.

• A 2022 crossover RCT (n=30) showed ghee raised ApoB by +9 mg/dL vs olive oil on average. Your response could be very different.

• Hyperproducers vs hyperabsorbers explains the variance. A sterol panel tells you which you are.

919 articles later, science shrugged

That wide range is a shrug. The cleanest direct comparison sharpens the picture a little. A crossover RCT compared ghee against olive oil for four weeks each and found ghee raised ApoB by +9 mg/dL and non-HDL cholesterol by +20.5 mg/dL, both statistically significant (British Journal of Nutrition, 2022; crossover RCT, n=30).

ApoB is the atherogenic particle count, the metric that predicts cardiovascular events better than LDL alone. The signal is real, but n=30 over four weeks is an average across a tiny group, not a prescription for any one person.

One reason the population data is so messy: decades of Indian epidemiological research is confounded by vanaspati. Starting in the 1960s, hydrogenated vegetable oil containing up to 40% trans fats was marketed across India as “vegetable ghee.” Many studies on “ghee consumption” never distinguished desi ghee from vanaspati. The most atherogenic dietary fat in history was literally sold under the same name, and in many Indian households, nobody knew the difference. When someone cites Indian studies on ghee, the first question should be: which ghee?

Three levers, all individualized

Three things decide whether ghee is a problem for you: the plate, your biology, and your numbers.

The plate. One teaspoon of ghee finishing a lentil dal is a completely different metabolic event than three tablespoons soaking a paratha with sweet chai. Same fat, different context. The fiber, the dose, the carbohydrate environment around the fat, that’s where the metabolic impact lives.

The numbers add up fast: one tablespoon of ghee delivers roughly 10 grams of saturated fat, half to three-quarters of most recommended daily limits. Traditional Indian cooking often uses two to four tablespoons per dish, and most people aren’t measuring. And many South Asians who “cut ghee” replace it with more roti and more rice, swapping saturated fat for refined carbohydrate, which doesn’t help and often hurts. The plate around the fat matters as much as the fat itself.

Your biology. The biggest split inside individual biology is hyperproducers vs hyperabsorbers. Hyperproducers make most of their cholesterol in the liver, largely independent of what they eat. Hyperabsorbers pull most of theirs from food and bile through the gut. The same plate of ghee hits these two phenotypes very differently.

It’s the same reason statins (which block production) are transformative for some patients and underwhelming for others, while ezetimibe and psyllium (which block absorption) are dramatic for one group and barely move the needle for another. Psyllium is what most South Asian households know as Isabgol. Dietary saturated fat is on the same axis. Whether ghee raises your ApoB depends on which side of this split you’re on.

Genetic variants (FTO, PPARG, TCF7L2, ApoE), family history, and current metabolic state layer on top of the phenotype. None of them are fully captured by population averages.

Your numbers. Genetics points the direction, family history sets the risk context, and the labs give the specifics. If you want to go deeper than ApoB, a sterol panel measures synthesis markers (lathosterol, desmosterol) and absorption markers (campesterol, sitosterol), and tells you which side of the hyperproducer / hyperabsorber line you’re on.

My genetic testing flagged a saturated fat intolerance cluster across four gene variants (FTO, PPARG, TCF7L2, PER2), and my father had a heart attack at 69. We swapped ghee for olive oil as our everyday cooking fat. Ghee still shows up for flavor when it matters, but the daily default changed. The swap is a part of a broader lipid management program.

The trial data won’t resolve this for you

The ghee vs olive oil RCT is small (n=30) and short (4 weeks). The meta-analysis is large but inconclusive. Better trials would help, but even a perfect population trial wouldn’t tell you what to do, because population averages hide the responder / non-responder split that’s the whole story.

Your own data already can. Get a baseline lipid panel with ApoB, change one variable, retest in 6-8 weeks. If you want to know the underlying mechanism, get a sterol panel and see which side of the hyperproducer / hyperabsorber line you’re on.

Myth: “Our grandparents ate ghee every day and lived to 90”

The Myth: Ghee has been a staple of Indian cooking for thousands of years. Our grandparents ate it daily and didn’t get heart disease. Modern dietary advice is Western nutrition science ignoring ancestral wisdom.

The Evidence: The ancestral argument cherry-picks one ingredient from a lifestyle package you no longer live. Your grandmother also walked miles a day, ate fewer total calories, consumed far less refined carbohydrate, and had no vanaspati in her kitchen. Ghee existed inside a completely different plate and a completely different life. You can’t isolate one variable and credit it with the outcome.

There’s also survivorship bias at work. You’re remembering the grandparents who lived to 90. Take Neil’s family: all four of his grandparents had heart attacks. India has one of the highest age-standardized CVD mortality rates in the world.

And the study this argument usually rests on (Malhotra’s 1967 observation of 1.15 million Indian railway workers, British Heart Journal, 1967; ecological study) has no individual-level data. Northern India ate more ghee and had less heart disease, but physical activity, urbanization, diet composition, and vanaspati exposure all differed between regions. It cannot establish that ghee prevented anything.

The cultural verdict on ghee depends entirely on where you’re standing. The grandmother who fed it to you, the mom who cut it out, the wife who calls it a superfood. Same ingredient, three opposite stories, all with conviction and none with your data.

The Verdict: It’s Complicated. Both “ghee is poison” and “ghee is fine” are blanket statements that ignore the variance the science actually shows. Your grandparents’ ghee existed inside a lifestyle you don’t live anymore, and “grandma ate it” tells you nothing about your biology. The honest answer for you lives in your labs, not in the culture war.

The ghee question doesn’t have a universal answer, and that’s what makes it useful. What it does to your numbers depends on your plate, your phenotype, and your labs. The cultural debate becomes a personal one, and the personal one is the one you can act on. Between the auntie, the cardiologist, and the American wife who calls it a superfood, there’s another voice worth listening to: your own data.

Disclaimer: The information provided in this article is for educational and informational purposes only. It is not intended as a substitute for professional medical advice, diagnosis, or treatment. Always seek the advice of your physician or other qualified healthcare providers with any questions you may have regarding a medical condition or wellness program. Reliance on any information provided in this article is solely at your own risk. The author and publisher of this article make no representations or warranties, express or implied, regarding the completeness, accuracy, reliability, suitability, or effectiveness of the information contained herein. The inclusion of specific products, services, or strategies in this article does not imply endorsement or recommendation. The author and publisher disclaim any liability for any adverse effects or consequences resulting from the use or application of the information presented. You are encouraged to consult with a qualified healthcare professional before making any changes to your diet, exercise routine, or lifestyle.

I stopped rosuvastatin because the metabolic cost was too high for someone already managing metabolic syndrome (covered in Part 1). Other people stop for muscle pain. Many never start because they’ve heard statins cause dementia, a worry the data doesn’t support: meta-analyses of randomized trials show no impact on cognition or dementia risk, and large observational studies have found a small reduction in dementia risk among statin users (Ott et al., Journal of General Internal Medicine, 2015; meta-analysis of RCTs).

For a while, I assumed my options were limited. They weren’t. Four FDA-approved drug classes now have cardiovascular outcome data, meaning they’ve been proven to prevent heart attacks and strokes, not just lower a number on a lab report. Most people who stop or avoid statins never hear about them. And one humble soluble fiber has real LDL-lowering evidence that slots in alongside these drug classes.

If you stopped a statin and haven’t replaced it with anything, you’re not alone. The “statins or nothing” framing is years out of date. Here’s what actually exists.

The Bottom Line

• Four non-statin drug classes now have cardiovascular outcome data: ezetimibe, PCSK9 inhibitors, bempedoic acid, and (partially) inclisiran

• Moderate statin + ezetimibe achieves similar LDL targets with 18% less diabetes risk than high-intensity statin alone

• PCSK9 inhibitors are now as low as $25/month with insurance

• Psyllium husk is the one non-drug adjunct with real LDL and ApoB data. Covered in Part 2 of this series.

• Every year of delayed LDL lowering compounds plaque buildup. Mendelian data shows roughly 3x more benefit from lifelong versus late-life lowering.

A $10 generic that made outcome trials boring

Ezetimibe (sold as Zetia) is the most accessible non-statin option and probably the most underappreciated. It blocks cholesterol absorption in the intestine through a different pathway than statins, so the effects are additive when combined.

IMPROVE-IT (NEJM, 2015; RCT, n=18,144) tested ezetimibe added to simvastatin in post-heart-attack patients. The result: a 6.4% relative reduction in the primary composite endpoint. That’s a real but modest benefit, which is why it never made headlines. The diabetes profile is what makes ezetimibe interesting for this audience. A pooled analysis of 4 cohort studies found that moderate statin + ezetimibe achieved similar LDL targets with 18% less new-onset diabetes than high-intensity statin monotherapy. Same destination, different metabolic cost.

Generic ezetimibe costs roughly $10/month. For someone concerned about statin side effects or diabetes risk, moderate statin + ezetimibe may be the smarter combination. Ezetimibe alone (about 18-20% LDL reduction as monotherapy) is also a real option for someone fully off statins, though the combination evidence is stronger. Worth asking about.

The injectable that costs less than you think

PCSK9 inhibitors (the antibody versions are sold as Repatha and Praluent) are the most powerful LDL-lowering tools available. They’re monoclonal antibodies that block PCSK9, a protein that normally breaks down LDL receptors on liver cells. Blocking PCSK9 means your liver clears more LDL from your blood, and the therapy is delivered as a subcutaneous injection every two to four weeks depending on dose.

The outcome data is strong. FOURIER (NEJM, 2017; RCT, n=27,564) showed a 15% reduction in the primary cardiovascular endpoint with evolocumab. ODYSSEY Outcomes (NEJM, 2018; RCT, n=18,924) showed a 15% reduction with alirocumab. Combined, that’s over 46,000 patients in landmark trials with hard endpoints. No diabetes signal in either trial, despite massive LDL lowering.

The cost story has changed dramatically. Repatha is available at $239/month through the AmgenNow direct-to-patient program (launched October 2025), roughly 60% below the list price. With some insurance coverage, co-pays can be as low as $25/month. The “$14,000/year” number that scared everyone off was 2015 pricing.

One caveat worth noting: inclisiran works differently from PCSK9 antibodies. It’s a small interfering RNA that silences PCSK9 production at the genetic level, which is why a single injection lasts about six months. The technology is genuinely novel and the side effect profile, in theory, should be minimal. But the cardiovascular outcome data isn’t in yet. ORION-4 (n=~15,000) is the phase 3 outcome trial that will answer whether LDL lowering translates into event reduction. Until that reports, inclisiran belongs in a different evidence category than ezetimibe, PCSK9 antibodies, or bempedoic acid.

Built for people who can’t take statins

Bempedoic acid (sold as Nexletol) is the newest option on this list and the most relevant for statin-intolerant patients. It works on the same cholesterol pathway as statins but upstream, and here’s the key difference: it’s a prodrug that activates only in the liver, not in skeletal muscle. No muscle activation means no myalgia, which is the side effect that sends most people to the supplement aisle in the first place.

CLEAR Outcomes (NEJM, 2023; RCT, n=13,970) was the first trial to show cardiovascular benefit in statin-intolerant patients specifically. The result: 13% reduction in major cardiovascular events. The diabetes profile was favorable, trending protective with no HbA1c or glucose increase. In a prespecified diabetes subgroup analysis, the benefit was even stronger: a 2.4% absolute risk reduction in major cardiovascular events (Lancet Diabetes & Endocrinology, 2024).

For someone who genuinely can’t tolerate any statin, bempedoic acid + ezetimibe is the combination with the strongest evidence base, achieving roughly 38% LDL reduction combined.

One practical wrinkle worth knowing before the appointment: with how insurance approvals work today, it’s now often easier to get a PCSK9 inhibitor covered than bempedoic acid, even for statin-intolerant patients. Coverage favors the drug class with longer and stronger outcome data, even when the newer option fits the clinical profile better. A small access reality that can flip the order of what you actually try first.

The soluble fiber that still earns its place

Before leaving the toolkit, the one non-drug adjunct: psyllium husk, what most South Asian households know as Isabgol. Part 2 of this series covered the evidence in detail (the meta-analysis, the mechanism, the dose, the cost, the cross-link to my deeper write-up). It belongs in any non-statin conversation, and it’s been part of my own regimen.

Every year you wait, your arteries remember

The urgency behind all of this comes from one concept: cumulative LDL exposure. Atherosclerosis is driven by the total LDL-years your arteries have experienced, not your LDL level today.

The data on this is striking. People born with genetic variants that naturally lower LDL by roughly 40 mg/dL from birth experience a 54.5% reduction in coronary heart disease risk (Ference et al., JACC, 2012; meta-analysis, n=312,321). That’s roughly three times the benefit seen when a statin delivers the same 40 mg/dL reduction starting in middle age, according to the same analysis. The European Atherosclerosis Society consensus confirms the effect is both causal and cumulative.

For South Asians, with coronary disease onset roughly 10 years earlier than European populations, the window for early treatment is narrower and the cost of delay is steeper. The question has shifted from “statin or nothing” to how soon, by how much, and with which tool.

How low is low enough?

Whatever you settle on, the next question is how aggressively to push the numbers. The 2019 ESC/EAS guidelines, still current as of the 2025 focused update, call for LDL below 55 mg/dL for very-high-risk patients (existing cardiovascular disease, diabetes with target organ damage, familial hypercholesterolemia) and below 40 mg/dL for those with recurrent events on maximum therapy (Mach et al., European Heart Journal, 2019; consensus guidelines). The American ACC/AHA guidelines sit at LDL below 70 mg/dL for similar profiles, moving in the same direction.

ApoB tracks alongside. The widely cited targets: below 80 mg/dL for high-risk and below 65 mg/dL for very-high-risk patients.

For South Asians, where 10-year ASCVD risk is systematically underestimated by standard calculators, the case for hitting the lower end is stronger. Practically: if you have a strong family history of early heart attack, stroke, or diabetes, treat yourself as “high risk” or “very high risk” even without a prior cardiac event of your own. The biology of cumulative LDL exposure is the same; the starting risk isn’t.

What these trials can’t tell us yet

The PCSK9 inhibitor and bempedoic acid trials enrolled predominantly white populations. South Asians are underrepresented in all four major outcome trials covered here. The direction of evidence is strong, but ethnic-specific benefit-risk ratios are estimated, not proven. Inclisiran’s outcome data (ORION-4) is still pending. And the optimal sequencing of non-statin therapies (which to try first, which combinations work best for which risk profiles) is still being worked out in clinical practice. The evidence base is expanding faster than the guidelines.

Myth: “If I can’t tolerate statins, there’s nothing else I can do”

The Myth: Statins are the only proven way to lower LDL and prevent cardiovascular events. If you get side effects, your choice is suffering through them or going unprotected.

The Evidence: The belief persists because of three things: guideline lag, provider inertia, and patient messaging that stopped at “take your statin.” Most primary care physicians trained when statins were the only game with outcome data, and guidelines take years to catch up with trial results. The cost narrative reinforced it, because PCSK9 inhibitors really were unaffordable in 2015. The evidence covered above tells a different story: three non-statin drug classes now have independent cardiovascular outcome data, costs have dropped dramatically, and one class was specifically designed for statin-intolerant patients. The toolkit changed. The conversation didn’t.

The Verdict: Statin intolerance is a real problem, but “nothing else works” hasn’t been true for years. The toolkit expanded while the narrative stayed frozen.

One Thing I Changed

For the past couple of years, Zetia plus psyllium husk did the heavy lifting. My ApoB went from a peak of 103 to 83 on that combination, without a statin in the picture. Recently I added Repatha, a PCSK9 inhibitor. Early days. I’m watching the numbers settle before deciding what the long-term regimen looks like.

The pattern across the full three-post arc is simple. Stopping one tool is not the same as stopping the work. The toolkit is bigger than most doctors will tell you, and the decisions are granular.

Disclaimer: The information provided in this article is for educational and informational purposes only. It is not intended as a substitute for professional medical advice, diagnosis, or treatment. Always seek the advice of your physician or other qualified healthcare providers with any questions you may have regarding a medical condition or wellness program. Reliance on any information provided in this article is solely at your own risk. The author and publisher of this article make no representations or warranties, express or implied, regarding the completeness, accuracy, reliability, suitability, or effectiveness of the information contained herein. The inclusion of specific products, services, or strategies in this article does not imply endorsement or recommendation. The author and publisher disclaim any liability for any adverse effects or consequences resulting from the use or application of the information presented. You are encouraged to consult with a qualified healthcare professional before making any changes to your diet, exercise routine, or lifestyle.

The second came when I looked up what was actually in the bottle. The active ingredient in red yeast rice is monacolin K. Monacolin K is chemically identical to lovastatin, a prescription statin. The “natural alternative” IS the drug, sold without the dosing consistency, purity testing, or regulatory oversight that the prescription version requires. When researchers tested twelve red yeast rice products, they found citrinin, a toxic mycotoxin linked to kidney damage, in four of them (Gordon et al., Archives of Internal Medicine, 2010; laboratory analysis).

That sent me down a rabbit hole on every supplement marketed as a statin replacement, and I applied the same question from Part 1: has this been proven to prevent heart attacks, or does it just move a number on a lab report? For almost all of them, the answer is “the second.” For one, the answer is different. Let me show you both.

The Bottom Line

• No “natural statin alternative” has a single large RCT showing it prevents heart attacks or strokes

• Red yeast rice IS lovastatin (a prescription statin) in unregulated form, with toxic contamination in 4 of 12 products tested

• Niacin was tested in 25,673 patients and caused more harm than benefit. Two large trials ended the enthusiasm.

• The FDA identified 776 supplements containing unapproved pharmaceutical ingredients from 2007-2016

• Psyllium is the one exception: real LDL and ApoB data, boring mechanism, part of my regimen. Covered in a dedicated section below.

If your red yeast rice “works,” you’re taking an unregulated statin

The paradox sharpens when you follow it to its conclusion: if your RYR product has enough monacolin K to lower your LDL, you’re taking a statin with no quality control over dose, purity, or contamination. If it doesn’t contain enough, it’s doing nothing.

The chemical identity isn’t a coincidence. The first statin was discovered in 1973, when a Japanese biochemist named Akira Endo isolated it from a Penicillium mold growing on rice at a Kyoto grain shop. Red yeast rice is rice fermented on a different fungus that makes monacolin K, a molecule structurally identical to lovastatin. Both came from fungi making compounds that block the same enzyme. What separates them is regulation: dose, purity, and outcome data.

The FDA recognized this two decades ago, ruling Cholestin (a popular RYR supplement) an unapproved drug in 1998 and warning consumers about unauthorized lovastatin in RYR products in 2007. The monacolin K content varies wildly across brands, which means your dose changes every time you open a new bottle. That citrinin contamination in 4 of 12 products isn’t a theoretical concern either. Citrinin is a mycotoxin linked to kidney damage.

The clinical evidence behind RYR is thin. The studies are small, short, and none have measured cardiovascular outcomes like heart attacks or strokes. Compare that to the statin outcome data from Part 1: over 100,000 patients across decades of randomized trials.

Here’s the practical absurdity: generic lovastatin costs $4-10/month with a prescription. It comes with regulated dosing, known purity, and decades of safety monitoring. The RYR supplement that contains the same molecule often costs more, with none of those guarantees.

Niacin had its chance. Two large trials ended it.

Niacin is the cautionary tale for this entire conversation. For years it was a mainstream cholesterol therapy, prescribed to raise HDL. Unlike most supplements on this list, it got tested in large, rigorous trials, and failed both.

AIM-HIGH (NEJM, 2011; RCT, n=3,414) tested extended-release niacin added to statin therapy. No reduction in cardiovascular events. The trial was stopped early for futility. HPS2-THRIVE (NEJM, 2014; n=25,673) was even more definitive: niacin plus laropiprant added to statin therapy showed no cardiovascular benefit and caused more side effects, including infections, bleeding, and new-onset diabetes.

Two trials, nearly 30,000 combined patients. Niacin improves the HDL number on your lab report. It does not prevent heart attacks.

Four more supplements, zero cardiovascular outcome data

Bergamot doesn’t work in rigorous trials. The 2024 placebo-controlled RCT (MDPI Foods, 2024; n=110) found no improvement on LDL or oxidative stress markers, despite earlier excitement from small Italian studies. No cardiovascular outcome data exists.

Plant sterols are the strangest case. They produce a real 8-10% LDL reduction, but Mendelian randomization studies have linked elevated circulating plant sterols with cardiovascular risk (Nutrients, 2023). Lowering LDL through this mechanism may not deliver the benefit the LDL drop implies, and no outcomes trial has tested whether it does.

CoQ10 is the most common “take this with your statin” recommendation, and the evidence doesn’t support it. The premise is logical (statins block CoQ10, so supplementing should reduce muscle pain), but meta-analyses of randomized trials show it doesn’t help (JAHA, 2018; n=1,776). The deeper finding from one NIH-funded trial: only 36% of patients with self-reported statin myalgia developed symptoms during blinded testing. The other 64% were reacting to the idea of the drug.

Over-the-counter fish oil isn’t the same as Vascepa. The STRENGTH trial (JAMA, 2020; RCT, n=13,078) of EPA+DHA combo found no cardiovascular benefit. Vascepa is a prescription purified EPA with outcome data from REDUCE-IT, but it’s a regulated drug, not a supplement.

Psyllium is the exception

Before closing the door on supplements entirely, one deserves a section of its own. Psyllium husk, what most South Asian households know as Isabgol, is the one supplement in this category with real LDL and ApoB data.

A meta-analysis of 28 trials found that 10.2g daily reduced LDL by an average of 13 mg/dL and also reduced ApoB (Jovanovski et al., American Journal of Clinical Nutrition, 2018; n=1,924). The mechanism is physical: psyllium forms a viscous gel in your gut that binds bile acids. Your liver, now short on bile acids, pulls cholesterol out of circulation to make more. The result is a reliable LDL drop that compounds when paired with other lipid-lowering therapy.

This is category-different from the supplement graveyard. It’s fiber: cheap, boring, and effective. It’s been part of my own regimen for over a year. Practical basics: 10g daily, mixed in a full glass of water, before meals. For the full protocol, brand selection, and the synergy with Zetia, see my deeper write-up on psyllium.

776 supplements, and nobody had to prove they worked first

The Dietary Supplement Health and Education Act of 1994 makes all of this possible. Under DSHEA, supplements don’t have to prove they’re effective or safe before being sold. The FDA can only act after harm has already been demonstrated.

The consequences are measurable. The FDA identified 776 supplements containing unapproved pharmaceutical ingredients between 2007 and 2016 (JAMA Network Open, 2018; regulatory analysis). Roughly 20% of those contained multiple unapproved drugs. A separate analysis across 13 countries found 14.8% of non-hormonal supplements contained undeclared anabolic steroids. Independent testing by ConsumerLab has found roughly one in three multivitamins fail quality standards.

I wouldn’t run a business without audited financial data. At some point I started asking myself whether I was applying the same standard to my cardiovascular health.

What absence of evidence actually means

To be fair, absence of evidence is not evidence of absence. Large cardiovascular outcome trials cost hundreds of millions of dollars, and without patent protection, no supplement manufacturer has the incentive to run one. That’s a real limitation of the system, not a mark against any individual product.

But the limitation doesn’t change the evidence standard. If you’re choosing between a treatment proven to prevent heart attacks in tens of thousands of patients and one that hasn’t been tested at that level, the gap is real regardless of why it exists.

Myth: “Natural supplements are safer than prescription drugs”

The Myth: Natural alternatives to statins are safer because they come from nature, have fewer side effects, and aren’t made by pharmaceutical companies.

The Evidence: Red yeast rice IS a pharmaceutical (lovastatin) sold without pharmaceutical quality control, with toxic citrinin contamination in 4 of 12 products tested (Archives of Internal Medicine, 2010). Niacin, when tested in a large trial (HPS2-THRIVE, n=25,673), caused more infections, bleeding, and new-onset diabetes than placebo. The FDA found 776 supplements with undisclosed pharmaceutical ingredients (JAMA Network Open, 2018). Meanwhile, generic statins ($4-10/month) have decades of safety data in over 100,000 patients, known side effect profiles, and regulatory oversight requiring ongoing adverse event reporting.

The Verdict: “Natural” is a marketing category, not a safety category. Unregulated supplements have less safety data, less quality control, and in some cases more dangerous contamination than the prescription drugs they claim to replace.

One Thing I Changed

The RYR experiment ended my curiosity about cholesterol supplements. Psyllium earned its place in my regimen; the rest went back to the shelf. When I read a supplement label now, I read it for what’s missing as much as what’s listed: the outcome data, the dose consistency, the contamination testing. That’s usually where the story is.

Disclaimer: The information provided in this article is for educational and informational purposes only. It is not intended as a substitute for professional medical advice, diagnosis, or treatment. Always seek the advice of your physician or other qualified healthcare providers with any questions you may have regarding a medical condition or wellness program. Reliance on any information provided in this article is solely at your own risk. The author and publisher of this article make no representations or warranties, express or implied, regarding the completeness, accuracy, reliability, suitability, or effectiveness of the information contained herein. The inclusion of specific products, services, or strategies in this article does not imply endorsement or recommendation. The author and publisher disclaim any liability for any adverse effects or consequences resulting from the use or application of the information presented. You are encouraged to consult with a qualified healthcare professional before making any changes to your diet, exercise routine, or lifestyle.

Then I looked at the actual data and realized I was asking the wrong question. “Do statins cause diabetes?” sounds like it has a yes or no answer. It doesn’t. The useful questions are different, and they changed how I think about this decision and about health decisions in general.

The Bottom Line

• “Do statins cause diabetes?” is the wrong question. Three better ones: what’s the tradeoff, which statin, and what’s the real alternative?

• The tradeoff: for every 1 diabetes case, 5.4 cardiovascular events prevented. 62% of new cases occur in people already near the diabetes threshold.

• Not all statins are equal: pitavastatin is glucose-neutral, atorvastatin carries the highest risk

• No supplement (red yeast rice, berberine, bergamot, niacin) has cardiovascular outcome data

For every diabetes case, five cardiovascular events don’t happen

The fear is real. Statins do increase diabetes risk. The largest meta-analysis on this, covering 13 trials and 91,140 patients, found a 9% relative increase in new-onset diabetes (Sattar et al., Lancet, 2010; meta-analysis, n=91,140). Over 4 years, for every 255 people treated, 1 additional diabetes case. But for every roughly 40 mg/dL drop in LDL, those same 255 people experienced 5.4 fewer major coronary events (heart attacks and coronary deaths). The ratio is 5:1 in favor of treatment, and it gets wider once you add in strokes and revascularizations.

The randomized evidence tells the same story. JUPITER, a trial that prospectively tracked diabetes alongside cardiovascular outcomes, randomized 17,603 people without diabetes to rosuvastatin 20mg or placebo (Ridker et al., Lancet, 2012; RCT, n=17,603). Rosuvastatin produced 270 new diabetes cases vs. 216 on placebo, a 25% relative increase. But the risk concentrated in people with baseline metabolic syndrome, impaired fasting glucose, BMI of 30 or higher, or HbA1c above 6%. In those without any of those risk factors, diabetes incidence was unchanged.

The 2024 CTT update made the picture even clearer. Using individual participant data from large, double-blind RCTs, it found that 62% of new diabetes cases occurred in people already in the top quarter of baseline glucose (CTT Collaboration, Lancet Diabetes & Endocrinology, 2024). The HbA1c increase was 0.06-0.08%, which is clinically trivial. The people developing diabetes on statins were already approaching the threshold, and the statin pushed them over a line they were walking toward. “Statins reveal diabetes” is closer to the truth than “statins cause diabetes.”

Here’s what makes this personal for anyone reading this newsletter: the people most at risk for statin-induced diabetes (those with prediabetes, metabolic syndrome, visceral obesity) are the same people who benefit most from statins, because their baseline cardiovascular risk is highest.

For South Asians specifically, the Pooled Cohort Equation underestimates our risk by more than 2-fold (predicted 4.8% vs. actual 6.8% 10-year ASCVD rate; Patel et al., Circulation, 2021; UK Biobank, n=8,124 South Asian within a cohort of 458,000). We develop coronary artery disease roughly 10 years earlier than white populations (and if you’re South Asian reading this, that math probably applies to your family too). The 5:1 ratio for a general population is probably more favorable for us, though we lack the ethnic-specific trial data to prove it.

Any time someone tells you a medication “causes” something, ask what’s on the other side. The scary number without the benefit number is half a story.

Seven drugs, not one

Most people treat “statin” as a single thing. It’s seven different drugs with seven different metabolic profiles.

The diabetes risk varies meaningfully between them. At one end: pitavastatin, which most people haven’t heard of. A distributed network analysis across 10 real-world databases compared pitavastatin to atorvastatin and rosuvastatin and found pitavastatin had a 28% lower risk of new-onset diabetes (Seo et al., Cardiovascular Diabetology, 2022; n=87,734 across 10 databases). Glucose-neutral in practice, effective LDL lowering, available generically.

At the other end, atorvastatin and rosuvastatin carry the highest diabetes risk among commonly prescribed statins. The same Seo analysis found the incidence rate was consistently higher on both than on pitavastatin across all 10 databases.

Dose matters too. High-intensity statins carry a 36% proportional increase in diabetes risk, while low-to-moderate intensity statins carry only 10% (CTT Collaboration, Lancet Diabetes & Endocrinology, 2024). This is a lever you can pull. A moderate-intensity statin combined with ezetimibe achieves similar LDL targets with 18% less diabetes risk than a high-intensity statin alone (pooled meta-analysis of 4 cohort studies). Same destination, different metabolic cost.

Which one? At what dose? Combined with what? Those are the questions that matter when a statin is on the table.

Your supplement hasn’t been tested against a heart attack

The instinct to try something natural first is understandable. I’ve had that conversation in my own family. But when someone chooses berberine over a statin, or red yeast rice over rosuvastatin, they’re making an evidence decision whether they know it or not. The question is: what standard of proof am I requiring before I bet my cardiovascular health on it?

Statins have cardiovascular outcome data in over 100,000 patients across decades of randomized trials. No supplement, not red yeast rice, not berberine, not bergamot, not niacin, has a single large RCT showing it prevents heart attacks or strokes. Some move a number on a lab report. None have been proven to prevent the event that number is supposed to predict.

What the statin-type ranking can’t tell us yet

The head-to-head diabetes risk comparison across statins comes primarily from observational data and network analyses, not from randomized trials designed to compare one statin against another on metabolic outcomes. The pitavastatin data is encouraging but based on smaller populations than the atorvastatin and rosuvastatin evidence. And South Asians are underrepresented in nearly all major statin trials, which means the ethnic-specific tradeoff ratio (likely more favorable than 5:1) is estimated, not proven. The direction of the evidence is clear. The precision will sharpen as more data comes in.

Myth: “Statins cause diabetes, so you’re trading one disease for another”

The Myth: Taking a statin means trading heart protection for a new metabolic problem. The diabetes risk cancels out the cardiovascular benefit.

The Evidence: The “trade” framing assumes the two risks are equivalent. They aren’t. The cardiovascular events statins prevent (heart attacks, strokes, cardiovascular death) are acute and often irreversible. The diabetes cases statins contribute to are concentrated in people who were already metabolically close to the threshold, with HbA1c increases of 0.06-0.08%, manageable with monitoring and lifestyle. One side of the trade is catastrophic. The other is a lab value that crossed a line it was approaching anyway. The 5:1 ratio covered earlier quantifies this: the benefit outweighs the risk by a wide margin, and the risk itself is not the diabetes most people picture when they hear the word.

The Verdict: The risk is real, but calling it a “trade” overstates the diabetes side and understates the cardiovascular side. The better question: which statin, at what dose.

One Thing I Changed

I stopped my rosuvastatin after it raised my fasting insulin and A1c. I did not stop lowering LDL. Zetia plus psyllium husk carried the work for over a year, dropping my ApoB from a peak of 103 to 83 and LDL from 127 to 74. I just switched to Repatha, a PCSK9 inhibitor. Early days. I’m waiting for the numbers to settle before deciding what the long-term regimen looks like.

The framing shift is what stuck with me. Yes-or-no rarely fits a health decision. The questions that do, and that I now bring to every one: what’s the tradeoff, which intervention, and what’s the real alternative.

Disclaimer: The information provided in this article is for educational and informational purposes only. It is not intended as a substitute for professional medical advice, diagnosis, or treatment. Always seek the advice of your physician or other qualified healthcare providers with any questions you may have regarding a medical condition or wellness program. Reliance on any information provided in this article is solely at your own risk. The author and publisher of this article make no representations or warranties, express or implied, regarding the completeness, accuracy, reliability, suitability, or effectiveness of the information contained herein. The inclusion of specific products, services, or strategies in this article does not imply endorsement or recommendation. The author and publisher disclaim any liability for any adverse effects or consequences resulting from the use or application of the information presented. You are encouraged to consult with a qualified healthcare professional before making any changes to your diet, exercise routine, or lifestyle.

When I calculated my HOMA-IR, a single score that quantifies insulin resistance, it came out to 5.54. Anything above 2.5 means insulin resistant. I was more than double that threshold, and no doctor flagged it.

That number connected directly to the fatty liver disease I’d had since age thirteen. Insulin resistance was driving the fat accumulation the whole time, and fasting insulin would have shown it years earlier than anything else in my labs. In our diagnostics post, we listed fasting insulin as one of the core markers. This is why.

The Bottom Line

• Fasting insulin rises 10-13 years before glucose or HbA1c becomes abnormal (Lancet, 2009; Whitehall II, n=6,538)

• 75% of glucose-normal people have abnormal insulin patterns (Kraft database, n=14,384)

• Track four numbers together: fasting insulin, fasting glucose, HbA1c, and HOMA-IR. Any one alone can miss what the others catch. HOMA-IR = (insulin x glucose) / 405. Above 2.5 = insulin resistant.

• A fasting insulin test costs $20-30. Most doctors don’t order it. Ask.

Your annual physical checks the last rung, not the first

Metabolic dysfunction works like a ladder. Insulin rises first, then triglycerides climb, HDL drops, and your liver starts storing fat. Years later, glucose and HbA1c finally move. Your annual physical checks the last rung. Fasting insulin checks the first.

The Whitehall II study tracked over 6,500 people for 13 years and found that future diabetics already had significantly lower insulin sensitivity 13 years before diagnosis (Lancet, 2009; prospective cohort, n=6,538). Glucose only spiked in the final 2-3 years. The body compensates for insulin resistance by pumping out more insulin, keeping glucose in range, until it can’t. Standard screening catches the final stage: when compensation fails and glucose finally spikes.

That’s where HOMA-IR comes in. It turns two numbers from a standard blood draw into one insulin resistance score: below 1.0 is optimal, above 2.5 is insulin resistant, and above 5.0 is severe. The formula is simple: (fasting insulin x fasting glucose) / 405. You can calculate it yourself from any lab that includes both numbers.

Why doesn’t your doctor order fasting insulin? Because it’s not in the ADA screening guidelines. The entire diabetes screening paradigm is built around glucose, which is the last thing to break, not the first. The test exists and costs $20-30. The guidelines just haven’t caught up.

The “normal” range is lying to you

The reference range on your lab report makes this worse. Most labs call anything between 2 and 18.4 µIU/mL normal, but a fasting insulin above 9.0 already identifies prediabetes in 80% of affected patients (Endocrine Practice, 2009; cross-sectional, n=2,000+). At 14.3 µIU/mL, my lab report said normal. I was already well into insulin resistance territory by functional standards.

For South Asians, the standard ranges are even more misleading. HOMA-IR values run 67% above European averages (Diabetologia, 2013; Ghouri et al., age- and BMI-matched, n=186). When both groups gained the same weight, South Asians lost insulin sensitivity at roughly five times the rate: a 38% decrease compared to 7% in white Europeans (Nature Metabolism, 2024; GlasVEGAS controlled feeding study, n=35). The margin for early detection is thinner, the consequences arrive sooner, and the standard cutoffs were built on a different population.

I’m obese, and my glucose said I was fine

I’ve been obese since childhood. I was diagnosed with fatty liver disease at thirteen. By any common-sense measure, something is clearly off metabolically. But look at the glucose and A1c columns below.

Date Insulin (µIU/mL) Glucose (mg/dL) HbA1c (%) HOMA-IR Feb 2023 14.3 - 5.3 - Sep 2023 13.1 - 5.2 - Dec 2023 26.7 84 5.6 5.54 Oct 2024 16.9 82 5.4 3.42 Dec 2024 13.6 92 5.2 3.09 Sep 2025 14.3 89 - 3.14 Jan 2026 8.2 78 5.2 1.58

Glucose never left the normal range. HbA1c barely moved. If you only looked at the standard panel, you’d say I was metabolically healthy. Meanwhile, fasting insulin was screaming. At its peak, my HOMA-IR hit 5.54, more than double the threshold for insulin resistance, and not a single doctor flagged it.

The numbers that caught the problem were the ones nobody ordered: fasting insulin and HOMA-IR. That’s how the test is designed.

What HOMA-IR can and can’t tell you

HOMA-IR is a fasting-only measure. It tells you nothing about what happens after a meal. Someone can have a normal HOMA-IR and still have terrible post-meal glucose spikes, which is what a CGM can reveal. The two work together: HOMA-IR catches the baseline, a CGM catches the response.

One caveat on the numbers themselves: if you get your insulin tested at two different labs, you might get two different results. The tests aren’t perfectly standardized yet. That’s fine. What matters is the trend over time at the same lab, not any single number. Pick a lab and stick with it.

An elevated HOMA-IR is a conversation with your doctor, not a self-diagnosis. It’s a screening tool that opens a door. I’m watching whether mine holds below 2.0 as I continue to lose weight.

Myth: “My glucose is normal, so I’m metabolically healthy”

The Myth: Your annual physical checks fasting glucose or HbA1c. If those numbers are normal, your metabolism is working fine. You’d know if something was wrong.

The Evidence: The Kraft database, validated across 14,384 patients with extended glucose-insulin tolerance tests, found that 75% of people with normal glucose had abnormal insulin patterns (Crofts et al., Diabetes Research and Clinical Practice, 2015; n=14,384). A study of 1,313 young adults in Mumbai found 30.5% had hyperinsulinemia with completely normal glucose, and among those with HbA1c below 5.7%, nearly 40% had stimulated insulin above 80 mIU/mL (Frontiers in Clinical Diabetes, 2023; n=1,313). Globally, 1 in 4 adults has insulin resistance (Frontiers in Endocrinology, 2025; meta-analysis, n=235,148). Most don’t know it because the test that catches it isn’t part of standard screening.

The Verdict: Normal glucose is the last domino to fall, not the first sign that everything is fine.

One Thing I Changed

I now test my fasting insulin in my quarterly draws, and track that along with HOMA-IR so I can get a better sense of my metabolic health over time.

Disclaimer: The information provided in this article is for educational and informational purposes only. It is not intended as a substitute for professional medical advice, diagnosis, or treatment. Always seek the advice of your physician or other qualified healthcare providers with any questions you may have regarding a medical condition or wellness program. Reliance on any information provided in this article is solely at your own risk. The author and publisher of this article make no representations or warranties, express or implied, regarding the completeness, accuracy, reliability, suitability, or effectiveness of the information contained herein. The inclusion of specific products, services, or strategies in this article does not imply endorsement or recommendation. The author and publisher disclaim any liability for any adverse effects or consequences resulting from the use or application of the information presented. You are encouraged to consult with a qualified healthcare professional before making any changes to your diet, exercise routine, or lifestyle.

My ALT was always elevated, and every doctor shrugged and repeated the same line. Nobody mentioned my heart. Nobody mentioned that my liver was both a symptom and an accelerator of a metabolic problem building across multiple organ systems.

It turns out that fatty liver, now called MASLD (metabolic dysfunction-associated steatotic liver disease), sits at the center of a metabolic cascade that connects to cardiovascular disease, Type 2 diabetes, and kidney disease.

The Bottom Line

• Fatty liver is now MASLD: renamed in 2023 to reflect that it’s a metabolic condition, not a drinking problem

• 34.7% of South Asians have MASLD, with rates as high as 48% at BMI ≥25 (JGH, 2025; 62 studies, n=40,745)

• MASLD and heart disease share the same metabolic root: insulin resistance. The liver amplifies the signal, with significantly higher cardiovascular risk even after adjusting for other metabolic factors

• Standard liver enzymes (ALT/AST) are normal in ~25% of patients with significant fatty liver

One in three South Asians has it, and most don’t know

The largest meta-analysis of MASLD in South Asians pulled 62 studies covering 40,745 people and found a prevalence of 34.7% in the general population, rising to 60% among those with Type 2 diabetes (Journal of Gastroenterology and Hepatology, 2025; systematic review and meta-analysis, n=40,745). The mean BMI of those South Asian patients was only 24.8, barely above the normal range.

Globally, about 19% of normal-weight individuals have MASLD, and lean MASLD is more prevalent in Asia than anywhere else. A mean BMI of 24.8 means many of these patients wouldn’t trigger screening under standard Western guidelines. You can be at a weight most doctors would call healthy and still have fat accumulating in your liver.

The fibrosis data is what concerned me most. South Asian MASLD patients had advanced fibrosis (scarring) at a rate of 14%, roughly double the rates found in European and American cohorts (JGH, 2025). Lower BMI, higher fibrosis rates, worse outcomes at every stage.

The liver is a metabolic amplifier

For years I thought of my fatty liver as a liver problem. It’s actually a signal that the entire metabolic system is under stress, and the liver both reflects that stress and makes it worse.

The mechanism works through insulin resistance, the common root. When the liver accumulates fat, it becomes less responsive to insulin, which drives dangerous cholesterol patterns (more small dense LDL, higher triglycerides, lower HDL), chronic inflammation, and elevated blood sugar. Those same pathways drive cardiovascular disease and diabetes independently. The liver sits in the middle, amplifying all of it.

A nationwide Swedish cohort study (n=10,422) found that MASLD patients had 67% higher cardiovascular risk with noncirrhotic fibrosis and 115% higher with cirrhosis, even after accounting for traditional cardiometabolic risk factors. But most of the excess risk comes from the shared metabolic drivers (insulin resistance, inflammation, visceral fat), not from the liver itself. The liver is an accelerator, not the root cause.

The connection to diabetes runs both directions. Up to 65-70% of people with Type 2 diabetes have MASLD, and 15-30% of MASLD patients develop Type 2 diabetes within five years. In the South Asian meta-analysis, prevalence among T2DM patients was 60% (JGH, 2025). South Asians already have 1.5-2x higher insulin resistance at the same BMI as European populations.

Your ALT might be lying to you

Two problems make MASLD harder to catch than it should be. First, approximately 25% of MASLD patients have completely normal ALT and AST levels (BMC Gastroenterology, 2020; meta-analysis, 11 studies, n=4,084). Many patients are asymptomatic with liver function tests that look fine. A normal ALT does not mean a healthy liver.

Second, the diagnostic criteria were redesigned in 2023 when NAFLD was renamed MASLD. The new criteria use a BMI threshold of 23 for Asian populations, not 25 (which, if you’re South Asian, probably applies to you or someone in your family). That single number means South Asians qualify for screening at a lower weight than other groups, but most primary care doctors are still using the old cutoffs.

The practical starting point is a FIB-4 score, which uses four numbers from a standard blood panel (age, ALT, AST, platelets) to estimate fibrosis risk with no extra blood draw. If you’ve had a DEXA scan, check your visceral adipose tissue number: elevated visceral fat is strongly associated with liver fat, and you may already have that data sitting in a report. FibroScan is the next step if staging is needed, but start with what’s accessible.

28 years and counting

My ALT has been elevated for 28 years, and the January 2026 result of 84 U/L is still nearly double the upper limit.

But my DEXA scans tell a clearer story than my liver enzymes. Visceral fat dropped from 5.5 to 3.89 lbs over the past year, and my CCTA (coronary CT angiography) in November 2024 showed zero coronary atherosclerosis despite 28 years of NAFLD. DEXA and CCTA track progress that liver enzymes miss. If I had relied on ALT alone, I would have assumed nothing was changing.

I’m on tirzepatide, a GLP-1/GIP dual agonist. GLP-1 receptor agonists significantly reduce liver fat (some studies suggest reductions of up to almost 50%) (Wang et al., 2025; systematic review, 25 RCTs, n=2,600). For a condition that had zero approved treatments for decades, there are now three on the table (resmetirom, semaglutide for MASH, and tirzepatide showing the highest efficacy in late-stage trials).

What the data can’t tell us yet

The 2025 South Asian meta-analysis has very high heterogeneity, with prevalence ranging from 18.5% in rural settings to 47.1% in urban ones. Detection method matters enormously, and these numbers will sharpen as more studies use standardized MASLD criteria.

The Mendelian randomization evidence on CVD causality is nuanced: genetic variants that cause liver fat (PNPLA3, TM6SF2) show weak or no causal link to heart attacks, suggesting that the liver fat itself isn’t the direct CVD driver. The inflammatory pathways that come with it likely are. The clinical implication is that treating the metabolic dysfunction (insulin resistance, inflammation, visceral fat) matters more than treating the liver in isolation.

Most MASLD is driven by insulin resistance and caloric excess. Genetic factors like choline metabolism can play a role (they do in my case), but they’re one pathway among many.

Myth: “Fatty liver is caused by drinking too much”

The Myth: Fatty liver disease is a consequence of heavy alcohol use. If you don’t drink, or barely drink, you don’t need to worry about it.

The Evidence: MASLD (metabolic, non-alcohol-related fatty liver disease) now affects 38% of all adults globally, up from 25% two decades ago (Hepatology, 2024; 92-study meta-analysis). It is more common than alcohol-related liver disease worldwide. The primary driver is insulin resistance and metabolic dysfunction, not alcohol. The 2023 renaming from NAFLD to MASLD explicitly addressed this confusion: the old name implied that the default fatty liver was alcoholic. The new name drops the alcohol framing entirely and centers cardiometabolic risk. Many of the South Asian patients in the meta-analysis had a BMI that most doctors wouldn’t flag, and many have never had a drink.

The Verdict: Busted. MASLD is a metabolic condition, not a drinking problem. Insulin resistance, visceral fat, and metabolic dysfunction are the primary drivers.

One Thing I Changed

I added a gut-liver axis probiotic to my morning routine, targeting the connection between gut barrier function and liver inflammation (this took me a surprisingly deep research rabbit hole to land on a specific strain). Too early for results, but I’m tracking ALT at my next draw.

Twenty-eight years with this condition, and I’m only now understanding the full picture of what it connects to. The liver, the heart, blood sugar, kidney function: they’re all part of the same metabolic story.

Disclaimer: The information provided in this article is for educational and informational purposes only. It is not intended as a substitute for professional medical advice, diagnosis, or treatment. Always seek the advice of your physician or other qualified healthcare providers with any questions you may have regarding a medical condition or wellness program. Reliance on any information provided in this article is solely at your own risk. The author and publisher of this article make no representations or warranties, express or implied, regarding the completeness, accuracy, reliability, suitability, or effectiveness of the information contained herein. The inclusion of specific products, services, or strategies in this article does not imply endorsement or recommendation. The author and publisher disclaim any liability for any adverse effects or consequences resulting from the use or application of the information presented. You are encouraged to consult with a qualified healthcare professional before making any changes to your diet, exercise routine, or lifestyle.

In our first post, we looked at why South Asians get heart disease a decade earlier than other populations, and why lifestyle alone doesn’t explain it. The natural next question is: what do you actually do about it?

It starts with knowing your numbers. Not the ones from a standard annual physical, which checks almost none of the markers that matter most for South Asians, but the right ones that help you establish a baseline and track what’s actually happening over time.

In this post, we go through the markers that matter, why they’re important, and how often to check them. The goal is to give you enough context to have an informed conversation with your doctor and to start building your own picture of your cardiometabolic health.

This is not medical advice. It’s what we think is worth testing, why each marker matters, and what we’ve learned from the data.

The blood work your annual physical skips

ApoB is the single most important lipid marker most doctors don’t order. It counts every atherogenic (plaque-building) particle in your blood. LDL cholesterol estimates how much cholesterol those particles carry, but ApoB tells you how many particles there are. Two people with the same LDL-C can have very different ApoB numbers and very different risk profiles. If we could only pick one lipid marker, it would be this one.

Lp(a) is a genetically determined cholesterol particle that you test once. You can’t diet or exercise it down. 25% of South Asians have elevated levels, and it accounts for 9.5% of heart attack risk in South Asians vs. about 4% in White populations (Circulation, 2019; INTERHEART Lp(a) sub-analysis, n=6,086). If your Lp(a) is high, it doesn’t mean you’re doomed. It means you manage everything else harder: ApoB, blood pressure, glucose. Knowing the number changes the strategy.

Fasting insulin is the one most doctors skip entirely. They’ll order fasting glucose, which is a snapshot of your blood sugar at one moment in time. The problem is that glucose can look normal for years while insulin climbs to compensate. By the time glucose is elevated, insulin resistance has been building for a while. Ask for both fasting glucose and fasting insulin every time. For South Asians, where prediabetes shows up nearly 8x more often by age 45 than in White peers (JAHA, 2026; MASALA/MESA, n=2,700), catching insulin resistance early is the difference between prevention and treatment.

HbA1c is a 90-day blood sugar average that smooths out the day-to-day noise. A single fasting glucose can be thrown off by what you ate the night before. HbA1c gives you the bigger picture. If you have a family history of Type 2 diabetes, this is the trend line that matters most quarter to quarter.

The full lipid panel (LDL, HDL, triglycerides) is where most doctors stop. For South Asians, the pattern to watch is high triglycerides combined with low HDL and small dense LDL particles, what cardiologists call atherogenic dyslipidemia. North Indians develop coronary artery disease at total cholesterol around 170 mg/dL (Indian Journal of Medical Research, 2007), a number most doctors would call normal. Triglycerides are also a useful cross-check against metabolic health: if they’re elevated, something is off with insulin signaling, regardless of what your glucose says.

hsCRP (high-sensitivity C-reactive protein) is a general inflammation marker. Inflammation is one of the drivers of atherosclerosis, and visceral fat is a common culprit. hsCRP moves with body composition: as visceral fat comes down, hsCRP tends to follow. It’s a signal that connects metabolic health to cardiovascular risk.

Homocysteine is an amino acid linked to cardiovascular risk and B vitamin metabolism. South Asians tend to run higher, partly due to higher prevalence of MTHFR variants and partly due to vegetarian diets that are low in B12. The fix is usually B vitamins, which is why we recommend also tracking B12, B6, and folate to make sure you’re actually replete. Elevated homocysteine is common and fixable, but you have to know it’s there.

Advanced lipid panel (NMR) is worth getting once a year. It breaks down particle count and size: LDL-P, small dense LDL, HDL particle number. Two people with the same LDL cholesterol can have very different risk profiles depending on how many particles they have and how big they are. That said, the markers that actually get treated are LDL and ApoB. If those are in a good place, the doctor isn’t going to treat the particle sub-fractions independently. The NMR gives context, but ApoB is where the clinical decisions happen.

The imaging that blood work can’t replace

Blood work tells you what’s in your bloodstream. Imaging tells you what it’s done to your arteries.

Coronary artery calcium (CAC) scan is a 10-minute CT scan, typically $75-150, and most places don’t require a referral. It measures calcified plaque in your arteries. MASALA data shows that 46% of South Asians under 50 already have detectable calcium (MASALA, PMC9830106). A score of 0 is reassuring. Anything above 0 tells your doctor how aggressive to be with prevention.

A Cleerly CCTA (coronary CT angiography) goes a step further, mapping both calcified and non-calcified plaque. It’s more expensive and involves contrast dye, so it’s not for everyone, but if you have significant family history, it gives a more complete picture than CAC alone.

DEXA scanning is one of the most underused tools in preventive health. Most people think of it as a bone density test, but a full-body DEXA shows body fat percentage, lean mass, and critically, visceral fat, the metabolically dangerous fat wrapped around your organs that drives inflammation and insulin resistance. A scale tells you your weight changed. A DEXA tells you what changed. At the same BMI, South Asians carry 30% more visceral fat than other populations (International Journal of Obesity, 2016; MASALA/MESA, n=906). The scale won’t catch that. A DEXA will.

Other relevant markers to consider

These aren’t the core cardiometabolic panel, but they each connect to the bigger picture.

Testosterone (free and total) matters more in your 40s than most men realize. Total testosterone is what most doctors check, but free testosterone is the fraction that’s actually bioavailable. A solid total number can mask low free testosterone. Low T affects body composition, insulin sensitivity, mood, and cardiovascular risk. Ask for both.

Estradiol and SHBG give context to the testosterone numbers. Estrogen matters in men too: too high or too low affects mood, body composition, and cardiovascular risk. SHBG (sex hormone binding globulin) binds testosterone and makes it unavailable, so it’s the context that makes the other hormone numbers make sense.

TSH, Free T3, Free T4 cover thyroid function. Most doctors only order TSH. Free T3 is the active hormone cells actually use, and TSH alone can miss subtle dysfunction. Ask for all three.

Ferritin and full iron panel (iron total, TIBC, transferrin, iron saturation) are important because ferritin depletes first, long before iron total or hemoglobin drop. Without the full panel, depletion doesn’t show up until it hits as fatigue and poor recovery.

Vitamin D deserves a mention because 84% of South Asian women are deficient. Darker skin, indoor lifestyles, and clothing coverage all contribute. Supplementation is common but the right dose varies by individual, so track quarterly until you find it.

Omega-3 Index and fatty acid panel measures whether supplementation is actually working. The target is an Omega-3 Index above 8%. The ratio between omega-6 and omega-3 tells you whether chronic inflammation is being fueled by diet.

TMAO (trimethylamine N-oxide) ties gut microbiome health to cardiovascular risk. It’s a newer marker and not many people track it, but given the cardiovascular focus of this newsletter, it’s worth knowing about.

eGFR is a kidney function check. Kidneys filter everything: supplements, medications, metabolic waste. If kidney function is declining, you want to know early.

What all and how often

Blood work

Imaging

Other markers to consider

How to get started

You don’t have to do all of this at once.

If you’re South Asian and haven’t done anything beyond a standard physical, start here: ApoB, Lp(a) (once), fasting insulin, HbA1c, and hsCRP. These five tests, added to your standard lipid panel, will tell you more about your cardiometabolic risk than most people learn in a decade of annual physicals. Most can be added to a standard blood draw by asking your doctor. If your doctor pushes back, services like Function Health, Marek Health, or a direct-to-consumer lab can run them without a referral.

From there, consider a CAC scan if you have family history or are over 35. Consider a DEXA if you want to know what’s happening under the surface with visceral fat and lean mass.

If you’re actively managing multiple risk factors, quarterly blood work timed with a doctor check-in is ideal. For someone in maintenance mode, twice a year or even annually is enough for most markers. Lp(a) is a one-time test. Calcium CT every 3-5 years. DEXA annually.

The point is to track the right things and establish a longitudinal record of your body so you can catch things in time.

Disclaimer: The information provided in this article is for educational and informational purposes only. It is not intended as a substitute for professional medical advice, diagnosis, or treatment. Always seek the advice of your physician or other qualified healthcare providers with any questions you may have regarding a medical condition or wellness program. Reliance on any information provided in this article is solely at your own risk. The author and publisher of this article make no representations or warranties, express or implied, regarding the completeness, accuracy, reliability, suitability, or effectiveness of the information contained herein. The inclusion of specific products, services, or strategies in this article does not imply endorsement or recommendation. The author and publisher disclaim any liability for any adverse effects or consequences resulting from the use or application of the information presented. You are encouraged to consult with a qualified healthcare professional before making any changes to your diet, exercise routine, or lifestyle.

Then my family made it personal. My dad had a heart attack at 69. The angiography revealed 90% blockage in three arteries and 60-70% in three others. His cholesterol was “normal.” His blood sugar was fine. A few years later, my mom’s cousin collapsed at the breakfast table after a morning run, mid-50s, never drank, never smoked, healthy weight. He died before the ambulance arrived. A few months ago, another family member, seemingly in good health, passed away in his car while driving to the hospital.

One in ten heart attacks in South Asian men happens before age 40, roughly 2-3x the rate in Western Europeans (Lancet, 2004; INTERHEART, n=27,000+). Not 60 or even 50, but forty. Dr. Namratha Kandula, who leads the MASALA study on South Asian heart disease, put it simply: “Everyone knows somebody who has had a heart attack at a young age. It’s very common.”

I started paying attention.

TL;DR

• South Asians experience heart attacks 10 years earlier than other populations (median first heart attack: age 53 vs. 63)

• Risk factors like prediabetes appear 8x more often by age 45 in South Asian men, even with healthier lifestyles

• A CAC scan at 35-40 can show whether plaque has started building, years before symptoms

• Standard risk calculators weren’t built for you. Ask for A1c, ApoB, Lp(a), and imaging.

A decade earlier, and lifestyle alone doesn’t explain it

The INTERHEART study found that the median age of first heart attack in South Asians was 53 years, compared to 63 in Western Europe and China (Lancet, 2004; case-control, n=27,000+). A full decade earlier. And 9.7% of South Asian men had their first heart attack before age 40, roughly 2-3x the rate in Western Europeans.

The MASALA study tracked South Asian Americans head-to-head against other ethnic groups and found that despite better diet quality, lower alcohol consumption, and comparable exercise levels, South Asians still carried dramatically higher cardiovascular risk (JAHA, 2026; MASALA/MESA cohort comparison, n=2,700).

South Asian men at age 45 were nearly 8x more likely to have prediabetes than White peers (30.7% vs. 3.9%), with metabolic risk factors appearing at significantly younger ages. The lifestyle was fine, but the biology underneath it wasn’t.

The ruler was built for a different population

At the same BMI, South Asians carry significantly more fat in the places that matter most: visceral fat wrapped around organs, fat deposited inside liver tissue, and fat threaded between muscles (International Journal of Obesity, 2016; MASALA/MESA cross-sectional, n=906). You can look lean and still have a fatty liver driving insulin resistance, and standard BMI cutoffs won’t flag it.

Your cholesterol panel is probably incomplete too. South Asians tend toward a pattern of high triglycerides, low HDL, and small dense LDL particles, what cardiologists call atherogenic dyslipidemia. North Indians develop coronary artery disease at total cholesterol around 170 mg/dL (Indian Journal of Medical Research, 2007), a level most doctors would call normal.

Then there’s Lp(a), a genetically determined cholesterol particle that 25% of South Asians have at elevated levels. It accounts for 9.5% of heart attack risk in South Asians vs. about 4% in White populations (Circulation, 2019; INTERHEART Lp(a) sub-analysis, n=6,086 cases). You can’t diet or exercise it down. The only move is to test it once, know your number, and if it’s high, manage everything else harder.

My ApoB was 103 and nobody blinked

When I finally asked for ApoB, the number that counts every atherogenic particle in your blood, mine came back at 103 mg/dL. My LDL-C at the time was 127 mg/dL, technically flagged high but not a number most doctors would lose sleep over (I know, I was surprised too). Through Zetia, tirzepatide, and psyllium husk, my ApoB is now 83 mg/dL and my LDL-C is 74 mg/dL.

In November 2024, I got a Cleerly CCTA, a coronary CT angiogram that maps plaque in your arteries. It showed my arteries are clean, and my CAC score came back at 0. Reassuring, but not permanent. I’ll repeat it in 3-5 years.

The numbers being good now isn’t the point. Nobody would have caught the problem if I hadn’t asked for the right tests, and I only knew to ask because I went looking.

Good studies, done on different populations

INTERHEART is a case-control study, not a prospective trial, so the 53 vs. 63 comparison has design limitations. The “one in ten before age 40” data is from the global INTERHEART study and may not map perfectly onto diaspora South Asians, though the MASALA study shows similar patterns in South Asian Americans.

Even after accounting for ectopic fat, lipids, and Lp(a), researchers found these factors don’t completely explain the elevated coronary calcium in South Asians (JAHA, 2017; MASALA sub-study, n=803). Something else is contributing, and the theories are still being debated. One possibility: generations of calorie scarcity shaped a metabolism that stores energy efficiently, now mismatched with modern abundance. A 2024 study found that South Asian men who gained weight lost 38% of their insulin sensitivity vs. 7% for European men gaining the same amount (Nature Metabolism, 2024; controlled overfeeding study, n=35). Another thread points to epigenetic inheritance, though this evidence is suggestive rather than conclusive.

The data doesn’t wait for the explanation. Only 3.16% of participants across 310 cardiovascular clinical trials were South Asian (JACC: Asia, 2025; systematic review, n=1M+). The treatment guidelines your doctor follows were largely built on data from other populations.

Myth: “If I eat right and exercise, I should be fine”

The Myth: Heart disease is a lifestyle problem. Maintain a healthy diet, stay active, don’t smoke or drink, and your cardiovascular risk is low.

The Evidence: The MASALA study found that South Asians with better diets and lower alcohol intake still carried dramatically worse cardiovascular risk than other ethnic groups. Munaf Patel is the human version of that data point. He had his first heart attack at 39. He changed everything afterward: diet, exercise, stress management. Eight months later, he had a second heart attack. His father died of heart disease in his 40s (Chicago Tribune, 2019).

Lifestyle absolutely matters, and it’s the first thing any cardiologist will recommend. But for South Asians, lifestyle alone isn’t enough. Our biology works against us in ways that diet and exercise can’t fully offset: excess visceral and liver fat at the same BMI, Lp(a) levels you inherited and can’t change, and an atherogenic lipid pattern that a standard panel doesn’t even measure.

The Verdict: Lifestyle matters, but for South Asians, biology sets a different baseline.

There’s no shortage of health content out there: newsletters, podcasts, longevity influencers. But almost none of it is written for the South Asian body. The dietary advice assumes a Western diet. The risk calculators were calibrated on European populations. The clinical trials enrolled almost no South Asians. And most of our community has no idea how different our risk profile actually is.

I’m writing Desi Vitals with my dear friend Dr. Karan Bhalla. Karan is a board-certified interventional cardiologist in Houston, Texas. He trained at Seth G.S. Medical College in Mumbai, did his cardiology and interventional fellowships at UTHealth McGovern, and co-founded Orion Medical, where he’s been practicing for over fifteen years. He’s a Fellow of the American College of Cardiology, past president of the Harris County Medical Society, and faculty at McGovern Medical School. He sees South Asian patients with exactly these risk patterns every day. I bring the patient side, Karan brings the clinical side, and together we aim to do the work of reading the research, talking to the experts, and synthesizing it into clear, actionable information so you don’t have to spend hours sorting through scientific papers and podcasts to figure it out yourself.

Desi Vitals is the newsletter we wish had existed when we first started paying attention. Evidence-based South Asian cardiometabolic health, written for our community, by people who’ve lived it.