Normal weight, hidden danger: new study seeks to unmask 'Skinny Fat' risk
NCT ID NCT07358533
First seen Jun 27, 2026 · Last updated Jun 27, 2026
Summary
This study looks at a condition called 'metabolically obese normal weight' (MONW), where people have a healthy BMI but too much body fat, raising their risk for heart problems and diabetes. Researchers will study 176 young women with normal weight, measuring body fat, blood markers, and blood vessel function. The goal is to find better ways to diagnose this hidden condition early.
What this could mean
Our plain-language read of the trial. This is informational only, not medical advice or a prediction.
- What this could lead to
- If successful, this could lead to better ways to identify people who are at risk for heart disease and diabetes even though they have a normal weight.
- What could go wrong
- This is an observational study, not a treatment trial. It may not find clear markers, and results may not apply to men or older women.
This is an AI summary of the original study and may miss details. Read our disclaimer.
Study facts
What this study's own registry entry says, in plain language.
- Participants
-
About 176 people
The number the study aims to enrol. It can still change while the study runs.
- Expected to start
-
Sep 2026
An estimate. Start dates often move.
- Expected to finish
-
Sep 2029
An estimate. End dates often move.
- Lead sponsor
-
Other sponsor
The registry's catch-all category, for sponsors it does not file as a company, a government agency, or a research network.
Who can take part
This study's own entry requirements. Only the study team can say for certain whether you qualify.
Who is studied
Healthy women aged 18-35 years with a normal body weight (BMI \<25 kg/m²) recruited from the West Pomeranian region (Poland).
- Ages
-
18 to 35 years
- Sex
-
Female participants only
- Healthy volunteers
-
Accepted
You do not need to have the condition being studied to take part.
Show the full entry requirements Hide the full entry requirements
Copied word for word from the study's registry entry, so the wording is the study team's rather than ours.
Inclusion Criteria: * Written, informed consent to participate in the research. * Gender: Female. * Age 18-35 years. * BMI in the range of 18.5-25 kg/m². Exclusion Criteria: * Thyroid disease. * Pregnancy or breastfeeding. * Eating disorders. * Polycystic ovary syndrome (PCOS). * Hormone therapy and/or use of hormonal contraceptives. * Smoking. * Metal or silicone implants (contraindication for DXA/body composition accuracy). * Vitamin and/or mineral supplementation. * Acute and/or chronic illnesses. * Type I or II diabetes, dyslipidemia, hypertension. * Use of hypolipemic, antihypertensive, antiglycemic, or insulin medications.
Get updates
Get notified about this study
Sign up to get updates when this study changes or when new studies for Metabolic syndrome are added.
Genom att skicka in godkänner du våra Användarvillkor
Conditions
The condition(s) this trial relates to.
As listed by the trial registrant
The condition terms exactly as the trial's registrant entered them.
How to take part
Only the study team decides who joins. These are the ways to reach them.
-
The places running it
1 site. The list below names each one and where it is.
-
The official record
ClinicalTrials.gov lists the study team's own contact details, including names and phone numbers. We don't republish those.
-
A doctor treating you
A doctor who knows your case can contact a study site on your behalf, and can tell you whether this study is worth pursuing at all.
Contacts and locations
Locations
-
Pomeranian Medical University in Szczecin
Szczecin, West Pomeranian Voivodeship, 70-204, Poland
More trials for these conditions
Other studies related to the condition(s) this trial covers.
- Which exercise dose best helps kids with metabolic syndrome?
- Can a weekly weight drug quiet gout attacks?
- Can a Once-Daily form of tacrolimus spare liver transplant patients from side effects?
- Ketogenic diet vs mediterranean diet: which better reshapes metabolism?
- Can tailoring bypass length improve weight loss surgery results?
- Can AI predict your lifespan from a short video?