Browse the evidence

The presence of cardiometabolic risk factor clusters (CMRFCs)—defined as BMI ≥ 25 plus two of diabetes, hypertension, or hyperlipidemia—results in significant direct medical expenditures independent of cardiovascular disease, totaling approximately $80 billion annually in the U.S.

If you have obesity plus two other metabolic risks (high blood pressure, high cholesterol, or diabetes), your healthcare costs are significantly higher than those with just one risk factor, even if you haven't had a heart attack. This cluster costs the U.S. economy roughly $80 billion a year, largely driven by prescription drugs. Early management of these clusters is critical to preventing the even higher costs of overt cardiovascular disease.

Acute muscle protein synthesis (MPS) response to resistance exercise is not quantitatively correlated with long-term muscle hypertrophy in individuals, meaning acute MPS measurements cannot predict individual hypertrophic outcomes.

Do not use acute muscle protein synthesis tests to predict your muscle growth potential. While MPS is necessary for growth, its acute magnitude does not predict how much muscle you will gain from training. Focus on consistent training volume and nutrition rather than trying to maximize acute MPS spikes.

Acute muscle protein synthesis measurements are useful for understanding mechanistic differences between exercise and nutritional interventions but are not sufficient to predict individual hypertrophic responses.

Use acute MPS data to compare the *potential* of different training or nutritional strategies (e.g., milk vs. soy), but do not use it to predict how much muscle a specific person will gain.

One-repetition maximum (1RM) tests and isokinetic peak torque (PT) tests produce conflicting results for assessing alterations in muscle strength, meaning they are not equivalent measures of individual responsiveness to resistance training.

Do not use different testing methods to evaluate the same training program. If you train with free weights or machines (isoinertial), test using 1RM on similar movements. If you use an isokinetic dynamometer, stick to that for tracking. Using 1RM to judge an isokinetic program (or vice versa) will likely lead you to believe the program failed or succeeded when it actually produced standard adaptations, just measured differently.

Systematically manipulating resistance training variables (load, volume, contraction type, rest intervals) does not produce greater muscle hypertrophy than a standard progressive resistance training protocol in trained young men, despite generating higher total training volume and slightly greater acute myofibrillar protein synthesis.

If you are a trained individual, you do not need to constantly vary your resistance training variables (like load, volume, or rest periods) to maximize muscle growth. A standard progressive resistance training program, performed with high effort (to failure), is just as effective for hypertrophy as a complex, variable program. Focus on consistency and progressive overload rather than frequent changes in exercise selection or parameters.

Mitochondrial dynamics, specifically regulated by Drp1-mediated fission, are essential for maintaining muscle stem cell (satellite cell) regenerative competence and metabolic health throughout adult life.

As you age, your muscle stem cells rely on healthy mitochondrial function to repair tissue. While you cannot directly 'dose' Drp1, you can support mitochondrial health through regular physical activity and adequate nutrition, which are known to promote mitochondrial biogenesis and dynamics. This biological maintenance is key to preserving muscle mass and regenerative ability in adulthood.

Higher circulating levels of the trans-fatty acid isomer trans/cis-18:2 (t/c-18:2) are associated with increased total mortality and coronary heart disease (CHD) incidence, but only after mutual adjustment for other TFA subtypes.

The isomer t/c-18:2 is linked to higher heart disease risk, particularly when other trans fats are accounted for. Since industrial trans fats (partially hydrogenated oils) are a major source of various trans isomers, avoiding these processed foods helps minimize exposure to potentially harmful isomers like t/c-18:2.

Transforming urban provisioning systems through integrated spatial planning and supply-side innovations (e.g., active mobility, green infrastructure, clean energy) reduces cardiometabolic risk factors and improves cardiovascular health outcomes.

Advocate for and utilize urban designs that prioritize walking, cycling, and access to green spaces. If you live in a city, look for 'walkable' neighborhoods with mixed land use. If infrastructure is lacking, support policy changes for better transit and pedestrian safety, as these systemic changes directly lower your risk of cardiovascular disease and help maintain a healthy weight.

Femoral subcutaneous adipose tissue exhibits significantly higher in vivo preadipocyte and adipocyte formation rates compared to abdominal subcutaneous tissue in women.

Your body's fat distribution is biologically determined. In women, thigh fat (femoral) tends to have higher cell turnover and expansion capacity than belly fat (abdominal). This is why lower-body fat is often considered more metabolically protective. You cannot change this genetic predisposition, but understanding it explains why fat accumulates differently in different areas.

In Mexican adults, general adiposity (BMI or height-adjusted weight) is a stronger independent predictor of blood pressure than central adiposity (waist circumference, waist-hip ratio, or waist-height ratio), with no evidence of threshold effects.

For Mexican adults, maintaining a healthy overall body weight is more critical for controlling blood pressure than focusing solely on waist size. Since there is no 'safe' threshold for adiposity, lower general body weight is consistently associated with lower blood pressure, regardless of where the fat is stored.

Supplementation with commercially available leucine metabolites (α-HICA, HMB-FA, or HMB-Ca) does not enhance resistance training-induced gains in muscle thickness, strength, or power in young, moderately trained men consuming a high-protein diet.

If you are a young, moderately trained man eating enough protein and training consistently, taking HMB or α-HICA will not give you better muscles or strength than if you just took a placebo. Focus on your training and diet instead of spending money on these supplements.

Co-administration of the GLP-1 receptor agonist liraglutide and nicotine synergistically lowers body weight in obese mice by simultaneously reducing food intake and increasing energy expenditure.

In obese mice, combining a GLP-1 drug (liraglutide) with nicotine resulted in greater weight loss than either drug alone. This happened because the combination reduced hunger more effectively and increased the body's energy expenditure. This suggests that for humans, smokers might experience enhanced weight loss from GLP-1 medications, or that specific nicotine-targeting strategies could boost GLP-1 efficacy.

Sleep duration is primarily determined by environmental factors with low heritability, whereas body composition measures (adiposity and lean mass) are strongly influenced by genetic factors with high heritability.

You cannot change your genetic predisposition to body fat or lean mass, which accounts for a large portion of your body composition. However, sleep duration is largely environmentally determined, meaning you have significant control over how much you sleep. This suggests that improving sleep habits is a viable lever for health, even if it doesn't directly dictate your genetic body type.

Higher body mass index (BMI) is independently associated with elevated plasma levels of acylcarnitines (ACs) and large neutral amino acids (LNAAs), serving as biomarkers of metabolic dysregulation and increased cardiometabolic risk.

Your weight (BMI) is a rough proxy for metabolic health, but it's not the whole story. This research shows that as BMI increases, your body's metabolic byproducts (specifically acylcarnitines and large neutral amino acids) also increase, signaling higher metabolic stress and disease risk. Focus on metabolic health markers and lifestyle factors rather than just the number on the scale.

Long-term weight loss maintenance is not significantly predicted by dietary adherence or caloric restriction, but is associated with baseline proteomic and gut microbiome signatures.

If you struggle to maintain weight loss despite good adherence, your baseline biology (proteins and gut bacteria) may be a factor. This suggests that personalized dietary strategies based on biological markers might be more effective than generic advice for long-term maintenance.

WB-EMS does not provide additional benefits for dynamic arm strength, balance, or flexibility in postmenopausal women compared to standard resistance and aerobic training.

Do not rely on WB-EMS to improve your balance, flexibility, or arm strength. Stick to traditional stretching and upper-body specific exercises for those goals. WB-EMS is best used as a tool to boost leg power and heart health when combined with standard exercise.

BMI is a non-specific composite index of risk that fails to distinguish between body fat and muscle mass, leading to misclassification of health risk in certain populations (e.g., athletes, different ethnicities).

If you are muscular or have a different body type, BMI might not reflect your health accurately. Use other measures like waist circumference or body composition analysis if possible. However, for the general population, BMI remains a useful, albeit imperfect, tool for assessing overall health risk.

There is no clinically relevant difference in individual response heterogeneity (variability in body mass change) between low-carbohydrate and low-fat diets.

If you are choosing between a low-carbohydrate and a low-fat diet for weight loss, do not expect one to be inherently more 'unpredictable' or variable in its results than the other. The variability in how much weight people lose is similar for both approaches. Therefore, the choice should be based on preference, adherence, and health markers rather than an expectation of superior or inferior individual response variability.

Aggregation of modifiable risk factors (hypertension, overweight/obesity, dyslipidemia, smoking) significantly increases the prevalence of stroke in middle-aged and elderly Chinese patients with type 2 diabetes.

If you have Type 2 Diabetes, managing your blood sugar is not enough to prevent stroke. You must aggressively manage your blood pressure, maintain a healthy weight, control cholesterol, and avoid smoking. The risk of stroke multiplies as you accumulate these risk factors.

Lifestyle interventions (diet and exercise) for diabetes prevention are discursively constructed around the assumption that weight loss is the primary, sufficient, and controllable mechanism for preventing type 2 diabetes, despite evidence that long-term diabetes incidence reduction is not guaranteed and mechanisms are often unspecified.

Do not assume that losing weight will automatically prevent diabetes, nor that your worth is tied to your ability to maintain a strict lifestyle. The science shows that while lifestyle changes help, they are not a guaranteed fix, and the biological mechanisms are complex. Focus on sustainable health behaviors rather than chasing weight loss as a moral imperative or a guaranteed cure.

Caucasian women with obesity exhibit significantly higher in vivo adipose triglyceride (TG) replacement and de novo lipogenesis (DNL) rates compared to African-American women.

This research highlights that the way your body handles fat storage and synthesis (lipid kinetics) may differ based on your race, even if your weight and BMI are similar to others. For Caucasian women with obesity, the study found higher rates of fat turnover and synthesis in fat tissue compared to African-American women. This doesn't mean you can't lose weight, but it suggests that metabolic responses to diet and exercise might vary. It underscores the importance of personalized approaches to health rather than assuming one-size-fits-all metabolic profiles.

Subcutaneous femoral (thigh) adipose tissue has significantly higher triglyceride (TG) replacement rates compared to subcutaneous abdominal (abdominal) adipose tissue in women with obesity.

Your body stores and processes fat differently depending on where it is. This study found that fat in your thighs (subcutaneous femoral) turns over (is broken down and rebuilt) faster than fat in your abdomen (subcutaneous abdominal). This might explain why some people find it easier to lose thigh fat than belly fat. It doesn't mean you can't lose belly fat, but it suggests that abdominal fat might be more 'stubborn' due to slower turnover rates.

Aligning dietary macronutrient prescriptions (moderate vs. low carbohydrate) to specific genetic polymorphisms (FABP2, PPARG, ADRB3, ADRB2) does not result in greater weight loss or body composition improvements compared to non-aligned diets in sedentary women with obesity.

If you are using a genetic test to choose between a low-carb and a moderate-carb diet for weight loss, do not expect the 'aligned' diet to give you an advantage. Both diets worked similarly well (or poorly) regardless of genetic alignment. Focus on sticking to a sustainable caloric deficit and exercise routine rather than spending money on genetic diet testing.

While a protein-polyphenol beverage accelerates early functional adaptations and increases type II fiber hypertrophy, it does not further increase peak isometric torque, overall muscle function, or total quadriceps muscle volume compared to placebo in the later stages of resistance training (sessions 10-30).

Don't expect this specific supplement to make you bigger or stronger than standard protein in the long run. The early boost in function and fiber size is nice, but for overall muscle volume and peak strength after the first month, it offers no advantage over a placebo or standard protein. You can likely stop the specialized polyphenol supplements after the initial adaptation phase.