Existing Skinny Fat Datasets?

What current real-world human skinny fat datasets exist? At present, as per our theory (1) that skinny fat is genetically deficient muscle, aside from our skinny fat dataset (2), no other datasets exist. The most robust population body-composition datasets are the UK Biobank (3) and the German National Cohort (NAKO)(4), whose existing and continued whole-body MRI scans have been analyzed to quantify selected muscle and adipose tissue (regular white/yellow body fat).

However, these datasets do not directly focus on skinny fat or establish each participant’s original biological starting point with respect to anatomical structure or muscle tissue. Nor do they comprehensively establish how each participant’s muscle tissue changed over time in response to diet, exercise, lifestyle, and aging. These are fundamental limitations when attempting to distinguish an underlying, genetically influenced phenotype from changes acquired throughout life.

A participant with relatively little muscle today may have naturally (genetically) developed less muscle initially, experienced muscle atrophy or age-related sarcopenia, or experienced some combination of these factors. Cross-sectional datasets cannot distinguish these possibilities on their own. Even longitudinal datasets like the UK Biobank study, which measure changes over time, have no standardized way to establish an individual’s developmental baseline or determine the extent to which observed changes resulted from genetic influences, diet, exercise, lifestyle, and/or aging.

Existing Skinny Fat Datasets?

In terms of the mainstream definition of skinny fat as normal-weight obesity (NWO) (5, 1), in 2026, researchers from institutions in Spain, including the University of the Balearic Islands (Universitat de les Illes Balears), published a cross-sectional study (6) focused on normal-weight obesity (NWO) using 12,874 adults aged 22-30 years. Participants underwent routine occupational health assessments via body composition proxies—BMI and waist-to-height ratio—to evaluate the prevalence of normal-weight obesity and its association with cardiometabolic risk markers. But the focus was entirely on adipose tissue. No muscle measurements were taken, and muscle was not even considered.

UK Biobank

A large, long-term biomedical database comprising approximately 500,000 UK volunteers recruited between 2006 and 2010, when they were aged 40–69, to investigate how genetics, lifestyle, and environmental factors influence health and disease. It is globally accessible to approved researchers and uniquely pairs comprehensive genetic data (including whole-genome sequencing) with decades of linked electronic health records, lifestyle questionnaires, physical biomarkers, and an ongoing multi-modal imaging sub-study of 100,000 participants. By merging deep biological profiles with real-time tracking of medical outcomes, it serves as one of the world’s most powerful resources for public health and medicine.

However, the study is not skinny-fat-focused and was not designed to measure (and entirely lacks) each participant’s initial anatomical starting points and early-life biological baselines. Furthermore, while the study has since integrated advanced whole-body MRI tracking to measure muscle volume and fat infiltration, these detailed imaging scans were introduced years after enrollment and only capture longitudinal changes for a smaller subset of the cohort. Because researchers primarily rely on mid-to-late-life snapshots rather than a biological starting point from a young age with continuous lifespan tracking, the available measurements alone do not definitively isolate the respective contributions of genetic influences, diet, exercise, lifestyle, and aging to an individual’s muscle development and subsequent changes.

German National Cohort (NAKO)

Germany’s largest long-term health study, tracking over 205,000 randomly selected adults between the ages of 20 and 69 years old (at recruitment) over a 20-to-30-year period, to investigate the causes, risk factors, and early detection of widespread chronic illnesses like cancer, diabetes, and cardiovascular diseases. Baseline examinations occurred between 2014 and 2019 across 18 centers, collecting an extensive repository of lifestyle questionnaires, medical measurements, biosamples, and whole-body MRI scans (providing detailed images of body fat distribution and the musculoskeletal system).

Participants are aging alongside the project. The project relies on regular follow-up surveys and re-examinations to provide researchers with a massive, high-quality data pool aimed at improving public health and personalized medicine. But it also lacks a skinny-fat focus and each participant’s early-life initial biological starting points/anatomical baselines.

Other Skinny Fat Datasets?

Another 2026 study (7) pooled data from both the UK Biobank and German National Cohort (NAKO) studies. It examined 66,608 participants to create age-, sex-, and height-adjusted reference curves for skeletal muscle volume, subcutaneous and visceral fat, muscle fat fraction, and intermuscular adipose tissue. These are genuine individual-level measurements extracted from MRI, but the study did not classify participants according to conventional normal-weight obesity (skinny fat)(3, 1) or our proposed skinny fat (genetically deficient muscle) theory (1).

Other relevant datasets include a study (8) of 102 adults in which MRI-based segmentation quantified 70 muscles and 13 bones, as well as population studies using inferior indirect measurement DEXA/DXA (9) scans to estimate lean body mass (LBM)(10) and adiposity. Honorable mentions include the NHANES US population body-composition data (11), Framingham Heart Study (12), and NHLBI Growth and Health Study (13). Although skinny fat was not a main or even mentioned variable in any of those studies. Moreover, measuring selected anatomical structures or comparing current body composition with population averages does not establish whether an individual’s muscular development was deficient from the outset or whether their current measurements reflect subsequent muscle tissue loss.

Consequently, while substantial real-world datasets do exist for studying muscle, fat, and their associations with health, the studies reviewed here do not establish a standardized, validated dataset specifically designed to investigate skinny fat as a genetically deficient muscle phenotype. The question of skinny fat requires a clearly operationalized, standardized baseline phenotype, an appropriate total muscle tissue measurement framework, and research capable of distinguishing underlying structural characteristics at birth through childhood from changes acquired over an individual’s lifetime. Which our MRI Study (14) aims to solve.

References

1. Skinny Fat Science: What Is Skinny Fat?, July 26, 2024. https://skinnyfat.fellowone.com/skinny-fat-science/what-is-skinny-fat/
2. Fellow One Research: Body Type Science Research Data. https://fellowone.com/category/fellow-one-research/the-four-body-types/body-type-science/body-type-quiz/research-data/
3. UK Biobank: The UK Biobank Initial Imaging Project, Participant information sheet – initial imaging pdf (1 MB), June 2024, Version 17.1. https://www.ukbiobank.ac.uk/taking-part/participant-opportunities/imaging-project/the-uk-biobank-initial-imaging-project/
4. The Federal Ministry of Research, Technology, and Space: German National Cohort (NAKO Health Study), MRI examination. https://nako.de/en/participating/examinations/mri-examination/
5. NIH, National Library of Medicine: Normal-weight obesity syndrome: diagnosis, prevalence, and clinical implications, September 2016 (Epub Jul 29, 2016), Lana P Franco, Carla C Morais, Cristiane Cominetti. https://pubmed.ncbi.nlm.nih.gov/27473199/
6. NIH, National Library of Medicine: Normal-Weight Obesity and Hidden Cardiometabolic Risk in Young Adults: Implications Beyond BMI-Based Classification, June 27, 2026. Alberto Ramírez Gallegos, Pedro Juan Tárraga López, Mónica Silu Piña Dabreu, Lluis Rodas Cañellas, Ángel Arturo López-González, and José Ignacio Ramírez-Manent. https://pubmed.ncbi.nlm.nih.gov/42506323/
7. NIH, National Library of Medicine: Body Composition in the General Population: Whole-body MRI-derived Reference Curves from Over 66 000 Individuals, May 2026, Matthias Jung, Marco Reisert, Hanna Rieder, Susanne Rospleszcz, Tobias Haueise, Tobias Pischon, Thoralf Niendorf, Hans-Ulrich Kauczor, Henry Völzke, Robin Bülow, Maximilian F Russe, Christopher L Schlett, Michael T Lu, Fabian Bamberg, Vineet K Raghu, and Jakob Weiss. https://pubmed.ncbi.nlm.nih.gov/42084507/
8. American Physiological Society, Journal of Applied Physiology: Big bones mean big muscles: an MRI-based dataset of muscle-bone-body size relationships across 70 human muscles of the upper limb, trunk, and lower limb, January 2026, Volume 140, Issue 1, Lara Riem, Megan Pinette, Olivia DuCharme, Valeria Pabon, Jacob Morris, Ashley Coggins, Liza Harold, Kathryn Eve Costanzo, Matthew Cousins, Raina Hein, Matt Rhodes, Eline Lievens, Rajvi Shah, Xue Feng, Savannah Benusa, Tim Breeding, Michael D. Nelson, Wim Derave, and Silvia S. Blemker. https://journals.physiology.org/doi/full/10.1152/japplphysiol.00772.2025
9. Skinny Fact Science: What Body Fat Percentage Is Skinny Fat?, July 16, 2025. https://skinnyfat.fellowone.com/skinny-fat-science/what-body-fat-percentage-is-skinny-fat/
10. Skinny Fact Science: Lean Body Mass (LBM) and Skinny Fat, June 3, 2026. https://skinnyfat.fellowone.com/skinny-fat-science/lean-body-mass-lbm-and-skinny-fat/
11. Centers for Disease Control and Prevention (CDC): NHANES Questionnaires, Datasets, and Related Documentation. https://wwwn.cdc.gov/nchs/nhanes/
12. Framingham Heart Study: Research Milestones. https://www.framinghamheartstudy.org/fhs-about/research-milestones/
13. NIH, National Lung, Heart, and Blood Institute: NHLBI Growth and Health Study (NGHS), March 20, 2020. https://biolincc.nhlbi.nih.gov/studies/nghs/
14. Skinny Fact Science: Scientific Skinny Fat MRI Study – Proving What Skinny Fat Is, March 26, 2025. https://skinnyfat.fellowone.com/skinny-fat-science/scientific-skinny-fat-mri-study-proving-what-skinny-fat-is/