Scientists discovered a way to measure how much fat you eat by looking at chemicals in your blood and urine. They studied 153 women after menopause and found that certain blood markers can accurately show how much saturated fat, unsaturated fat, and omega-3s a person consumes. This is important because doctors have struggled to measure fat intake accurately in the past. The new method could help researchers better understand how different types of fat affect women’s health and disease risk over time.

The Quick Take

  • What they studied: Can scientists use blood and urine tests to figure out how much fat someone eats, and what types of fat?
  • Who participated: 153 postmenopausal women (women past their reproductive years) from the Women’s Health Initiative study who ate their normal diets while researchers tracked their food intake
  • Key finding: Blood tests successfully predicted how much of most types of fat women were eating, with accuracy ranging from 31% to 65% depending on the fat type. The most accurate predictions were for short-chain fats (like butyric acid) and omega-3 fats (like DHA).
  • What it means for you: In the future, doctors may be able to order a simple blood test instead of asking you to keep detailed food diaries to understand your fat intake. This could help identify which women might benefit from changing their fat consumption to reduce disease risk, though this research is still in early stages.

The Research Details

Researchers conducted a controlled feeding study where 153 postmenopausal women ate their regular diets while scientists carefully measured everything they consumed. The researchers collected blood samples and 24-hour urine samples (all urine collected over one full day) from each woman. They then used statistical methods to find patterns between the chemicals found in the blood and urine and the actual amounts of different fats the women had eaten. This allowed them to create mathematical equations that could predict fat intake from blood and urine test results.

The study focused on different types of fat: saturated fats (like butter and coconut oil), monounsaturated fats (like olive oil), and polyunsaturated fats (like fish oil and vegetable oils). They also looked specifically at omega-3 and omega-6 fatty acids, which are important for health. The researchers used a technique called cross-validation, which means they tested their equations on different groups of women to make sure the predictions worked accurately.

Measuring what people actually eat is one of the biggest challenges in nutrition research. Food diaries are unreliable because people forget what they ate, guess at portion sizes, or change their eating habits when they know they’re being watched. Blood and urine tests would be objective—they show what your body actually processed, not what you remember eating. This study matters because it shows these tests might work for measuring fat intake specifically, which is important since different types of fat affect health differently.

This study has several strengths: it used a controlled feeding study (the gold standard for nutrition research), it measured actual food intake carefully, and it tested multiple types of fats. However, the study only included postmenopausal women, so results may not apply to younger women, men, or other groups. The sample size of 153 is moderate—larger studies would provide more confidence. The study was published in a highly respected nutrition journal, which suggests it passed rigorous scientific review.

What the Results Show

The researchers successfully created blood test equations that could predict how much of most types of fat women were eating. For saturated fats, the predictions were quite accurate—explaining 35% to 65% of the variation in fat intake depending on the specific type. Myristic acid (a saturated fat found in dairy and meat) had the best prediction at 61%, while stearic acid (found in chocolate and beef) was less accurate at 34%.

For unsaturated fats, the results were more mixed. Oleic acid (the main fat in olive oil) could be predicted with 31% accuracy. For polyunsaturated fats, the predictions were better—linoleic acid (found in vegetable oils) was predicted with 52% accuracy, and DHA (an omega-3 fat from fish) was predicted with 48% accuracy.

When researchers combined multiple blood markers together, they could predict total saturated fat intake with 46% accuracy, total polyunsaturated fat with 53% accuracy, and total omega-3 fats with 46% accuracy. Most of the useful information came from serum metabolites (chemicals in blood), though urine markers also contributed. The equations also included information about how many calories each woman burned daily.

The study found that different types of fat left different ‘fingerprints’ in the blood. Some fats were easier to detect than others—short-chain saturated fats like butyric acid (found in butter) were among the easiest to predict at 65% accuracy. The researchers also discovered that combining information from multiple blood markers worked better than using any single marker alone. Additionally, the study confirmed that the blood markers met important scientific criteria for being reliable biomarkers, meaning they were specific to the fats being measured and didn’t get confused with other dietary components.

Previous research has shown that blood fatty acid levels reflect what people eat, but this is the first study to systematically develop equations that can predict specific fat intake amounts from blood and urine markers in a large group of women. Earlier studies looked at individual fatty acids but didn’t create comprehensive prediction equations. This research builds on decades of work showing that blood phospholipids (fat-containing molecules) reflect dietary fat intake, but goes further by creating practical tools that could be used in future studies.

The study only included postmenopausal women, so the results may not apply to younger women, men, or other groups. The accuracy of predictions varied widely depending on the type of fat—some were predicted quite well while others were not. The study didn’t include dietary supplements, so if someone takes fish oil pills, the blood tests wouldn’t capture that. The prediction equations explained at most 65% of the variation in fat intake, meaning other factors not measured in this study also influence blood fat markers. Finally, this was a relatively small study with 153 women, so larger studies would be needed to confirm these findings work in different populations.

The Bottom Line

This research is still in early stages and shouldn’t change your eating habits yet. However, it suggests that in the future, blood tests might become a useful tool for nutrition research and possibly for personalized health recommendations. If you’re interested in understanding your fat intake, current methods like food tracking apps or working with a dietitian remain the most reliable approaches. The confidence level for these findings is moderate—the research is promising but needs confirmation in larger, more diverse groups.

This research is most relevant to nutrition scientists and researchers who study how diet affects disease. It may eventually be useful for doctors who want to understand their patients’ fat intake without relying on memory. Postmenopausal women should be most interested since this study focused on that group. People interested in personalized nutrition and precision medicine should follow this research as it develops. However, this research is not yet ready for use in clinical practice or for changing individual dietary recommendations.

This is foundational research, not a treatment or intervention. There’s no timeline for ‘seeing benefits’ because the study doesn’t test whether changing fat intake based on these tests improves health. If these biomarkers are validated in future studies, it might take 3-5 years before they’re used in research studies, and potentially 5-10 years before they might be available for clinical use.

Want to Apply This Research?

  • Track your daily fat intake by type (saturated, unsaturated, omega-3) using the app’s food logging feature. Set a baseline for one week, then compare weekly averages over the next month to identify patterns in your fat consumption.
  • Use the app to identify which foods contribute most to your saturated fat intake, then experiment with one substitution per week (for example, replacing butter with olive oil, or red meat with fish once weekly). Log the change and track how it affects your total fat profile.
  • Create a monthly report showing your fat intake trends by type. Set reminders to review your omega-3 intake specifically, since this fat type is often under-consumed. Compare your patterns across seasons to see if your fat intake changes with food availability.

This research describes early-stage development of blood tests to measure fat intake. These biomarkers are not yet available for clinical use and should not be used to make personal health decisions. The study was conducted only in postmenopausal women and results may not apply to other populations. Always consult with a healthcare provider or registered dietitian before making significant changes to your diet based on any research. This study does not establish that changing fat intake based on these tests will improve health outcomes.