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Causes, Characteristics, and Consequences of Metabolically Unhealthy Normal Weight in Humans
Open accessAbstract
A BMI in the normal range associates with a decreased risk of cardiometabolic disease and all-cause mortality. However, not all subjects in this BMI range have this low risk. Compared to people who are of normal weight and metabolically healthy, subjects who are of normal weight but metabolically unhealthy (∼20% of the normal weight adult population) have a greater than 3-fold higher risk of all-cause mortality and/or cardiovascular events. Here we address to what extent major risk phenotypes determine metabolic health in lean compared to overweight and obese people and provide support for the existence of a lipodystrophy-like phenotype in the general population. Furthermore, we highlight the molecular mechanisms that induce this phenotype. Finally, we propose strategies as to how this knowledge could be implemented in the prevention and treatment of cardiometabolic diseases in different stages of adiposity in routine clinical practice.
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“skeletal muscle insulin resistance, affecting most persons with obesity, contributes to reduced muscle mass and poor muscle quality-a phenomenon observed in sarcopenic obesity.18,19”
From Changes in lean body mass with glucagon‐like peptide ‐1‐based therapies and mitigation strategies (2024) · cites this paper as [18]
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“Estos pacientes delgados, pero metabólicamente enfermos, presentan un perfil metabólico desfavorable, que se caracteriza por altos niveles de insulino-resistencia, alta prevalencia de hipertensión arterial y un perfil lipídico e inflamatorio desfavorable,(23) y pueden presentar acumulación de grasa ectópica, predomina…”
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“In addition, some composite risk scores require multiple parameters or rely on self-reported information, which may limit their applicability in large-scale population assessment (5, 6).”
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“…with the metabolically unhealthy normal-weight (“lean”) phenotype; recent work shows that cardiovascular risk indices, including TyG-derived indices and the atherogenic index of plasma, are significantly higher in MUHO than in metabolically unhealthy normal-weight (MUHNW) individuals [53,60].”
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“It does not distinguish between fat and lean mass, fails to reflect fat distribution, and does not adequately capture cardiometabolic risk [7].”
Li, Y., Liu, X., Shang, L., Wang, Y., Chen, Z., Yang, Y., & He, L. (2026) · Diabetes Obesity and Metabolism · doi:10.1111/dom.71235
Azimi, A., Atlas, K., Reeves, A., Zhang, C.-Y., Wasserthal, J., Mirjalili, S. R., Atlas, T., Henschke, C., Yankelevitz, D., Zulueta, J. J., et al. (2026) · Radiology: Cardiothoracic Imaging · doi:10.1148/ryct.250214
Nagy, R., Bombera, B., Szepesi, C. I., Horváth, N., Rekenyi, V., & Kolozsvári, L. (2026) · Life · doi:10.3390/life16081336
“…proposed basis is a limited capacity for safe subcutaneous fat expansion—determined by adipocyte hyperplasia, sex, genetic background and physical activity—so that when energy surplus exceeds that capacity, lipid is deposited viscerally and ectopically at a relatively low total body weight [37,41].”
Cheng, Z.-H., Gao, L., Hu, X.-D., Guan, W.-J., Cao, T.-Y., Liu, L.-S., Zhang, Y., Li, J.-P., Huo, Y., Cheng, X.-S., et al. (2026) · BMC Cardiovascular Disorders · doi:10.1186/s12872-026-06327-1
“A plausible explanation is the metabolically obese normal-weight phenotype, wherein individuals without overt obesity may still exhibit ectopic fat accumulation, insulin resistance, dyslipidemia, and an increased cardiometabolic risk [54, 55].”
Yemlihalıoğlu, H. N., Çapar, A. G., & Oğuzhan, A. (2026) · British Journal of Hospital Medicine · doi:10.31083/bjhm50330
Kawamoto, R., Kikuchi, A., Ninomiya, D., Abe, M., & Kumagi, T. (2026) · Diabetology & Metabolic Syndrome · doi:10.1186/s13098-026-02245-6
Wang, Z., Tan, C., Lyu, Z., Wen, Z., Wu, T., Geng, D.-F., & Zheng, S. (2026) · BMC Cardiovascular Disorders · doi:10.1186/s12872-026-06298-3
“Impaired proliferation and expansion of subcutaneous adipose tissue lead to chronic dysfunction of fat storage in white adipose tissue, resulting in ectopic fat deposition [25].”
Ke, J., Zhang, Y., Shao, X., Tan, Z., Bai, G., Ju, J., Chen, H., Wang, Z., & Zhang, J. (2026) · Diabetes Obesity and Metabolism · doi:10.1111/dom.71112 · Cited by 3
Semagn, B. E., Beune, E., Meeks, K., van der Linden, E. L., Schulze, M., & Ndaago, A. I. (2026) · BMJ public health · doi:10.1136/bmjph-2025-004485
Lee, Y.-S., Park, A. S. I., & Youn, B.-Y. (2026) · Preventive Medicine Reports · doi:10.1016/j.pmedr.2026.103550
“Individuals with NWO have been reported to exhibit insulin resistance, adverse lipid profiles, and chronic low-grade inflammation similar to those observed in individuals with obesity (Romero-Corral et al., 2010; Stefan et al., 2017).”
Lu, J., Cai, W., Fang, D., Bi, Y., & Gu, T. (2026) · The American Journal of the Medical Sciences · doi:10.1016/j.amjms.2026.06.009 · Cited by 1
Issever, K., Oral, A., Genç, A. C., Solmaz, İ., Koca, N., Topaloğlu, U. S., Demir, İ., DÜNDAR, A., Kırık, A., BAŞCI, Ö. K., et al. (2026) · Journal of Clinical Medicine · doi:10.3390/jcm15103794
Patterns of dietary habits are associated with metabolic health status in adults
Balali, A., Poursalehi, D., Heidari, Z., Rouhani, P., Shahdadian, F., Hajhashemy, Z., Mohammdi, S., Mokhtari, E., & Saneei, P. (2026) · British Journal of Nutrition · doi:10.1017/s0007114526106722
Shi, Z., Xu, Q., Yin, R., Zhou, Q., & Wu, C. (2026) · Metabolic Syndrome and Related Disorders · doi:10.1177/15578518261446293 · Cited by 1
“28,29 However, our correlation analyses revealed a more nuanced picture: gynoid fat displayed signi fi cant positive correlations with several atherogenic markers — particularly TC and 2 hr-PG — that were similar in direction to those observed for android fat.”
Pathophysiologie der mit metabolischer Dysfunktion assoziierten steatotischen Lebererkrankung
Kantartzis, K. (2026) · Die Diabetologie · doi:10.1007/s11428-026-01459-6
Xu, H., Wu, Q.-F., Huang, Z., Chen, L., & Li, X. (2026) · Diabetology & Metabolic Syndrome · doi:10.1186/s13098-026-02127-x
“These findings align with and extend the emerging concept of “metabolically unhealthy non-obese” pheno-typesby explicitly quantifying the risk gradient within the underweight category itself [6].”
Maternal PM2.5 exposure induces insulin resistance in adult male mouse offspring via gut–liver axis
Hu, R., Zhao, W., Fan, W., Li, R., Zhang, L., Qin, L., Zhu, H., Zhu, X., Sun, Q., Qiang, G., et al. (2026) · Particle and Fibre Toxicology · doi:10.1186/s12989-026-00676-7
“Previous studies have mainly focused on obesity-related metabolic disorders, largely neglecting the metabolically unhealthy normal weight (MUHNW) phenotype, which affected approximately 20% of individuals with normal weight [2].”
Zaragoza-García, Ó., Gutiérrez-Pérez, I. A., Villafán-Bernal, J. R., Delgado‐Floody, P., Alarcón-Paredes, A., Sánchez-Alemán, M. Á., Rodríguez-García, R., Navarrete, F. C., & Guzmán‐Guzmán, I. P. (2026) · Journal of Diabetes & Metabolic Disorders · doi:10.1007/s40200-026-01905-8
“…from the definitions of metabolic abnormalities, as well as the definitions for obesity according to body mass index or waist circumference [ 8, 9], therefore, some criteria identify more MU subjects due to different cut-off values for defin - ing obesity or impaired metabolic parameters [6 , 12 ].”
Ll, Z., Chen, N., Wang, Y., & Pan, T. (2026) · European journal of medical research · doi:10.1186/s40001-026-04125-1
Minato-Inokawa, S., Tsuboi-Kaji, A., Honda, M., Takeuchi, M., Kitaoka, K., Kurata, M., Wu, B., Kazumi, T., & Fukuo, K. (2025) · Scientific Reports · doi:10.1038/s41598-025-21340-8
Ramachandra, S. C., Prashant, A., & Vishwanath, P. M. (2025) · International Journal of Health & Allied Sciences · doi:10.4103/ijhas.ijhas_215_25
Kim, B. (2025) · Daehan imsang geon-gang jeungjin hakoeji/Daehan imsang geon'gang jeungjin haghoeji · doi:10.15384/kjhp.2025.00108
“The incidences of cardiovascular disease and all-cause mortality for these individuals are even higher than those of their metabolically healthy counterparts with a BMI ≥25 kg/m 2 [6,7].”
Wang, J., Wang, J., Lei, Y., Yuan, Q., Yin, X., & Zheng, F. (2025) · Frontiers in Nutrition · doi:10.3389/fnut.2025.1642725
“Although the mechanism underlying the TyG index and its changes in relation to MOMN and MNNW-MONW transition remain unclear, it may be partially elucidated from the perspective of insulin resistance, which is currently recognized as the key etiology of MONW (2, 4).”
Evaluation of body-mass index in patients with coronary artery ectasia
Memioğlu, T., Inanir, M., Dıramalı, M., Kiriş, S. V., Güven, I., Argana, K., Toprak, K., & Özyaşar, M. (2025) · Anatolian Current Medical Journal · doi:10.38053/acmj.1692331
Genética de los fenotipos metabólicos de la obesidad
Olivares-Arévalo, M., Villamil-Ramírez, H., López-Contreras, B., León-Mimila, P., Villarreal-Molina, M. T., & Canizales-Quinteros, S. (2025) · Gaceta Médica de México · doi:10.24875/gmm.24000399
Haider, M. A., Maria, M., Rauf, K., & Ali, H. (2024) · DEVELOPMENTAL MEDICO-LIFE-SCIENCES · doi:10.69750/dmls.01.10.042
“…be seemingly slim, according to conventional anthropometric standards, but with a different metabolic profile, they are high - risk patients with a likelihood of developing type 2 diabetes mellitus, hypertension, non - alcoholic fatty liver disease (NAFLD), and early cardiovascular events [2,3].”
Stefan, N., Yki‐Järvinen, H., & Neuschwander‐Tetri, B. A. (2024) · The Lancet Diabetes & Endocrinology · doi:10.1016/s2213-8587(24)00318-8 · Cited by 470
Self-citationNaibaho, J., Dieny, F. F., Murbawani, E. D., Fitranti, D. Y., & Tsani, A. (2024) · Food Research · doi:10.26656/fr.2017.8(6).572
“Individuals with a body mass index (BMI) within the normal range are considered healthier and have protective factors in reducing premature mortality risk (Stefan et al ., 2017).”
A Novel and Comprehensive Wellness Assessment for Lifestyle‐Based Interventions
Ellison, K. M., Smith, K. A., Fernández, J. R., Plaisance, E. P., Chui, T. K., Hill, J. O., Wyatt, H. R., & Sayer, R. D. (2024) · Obesity Science & Practice · doi:10.1002/osp4.70022
Zhu, X., Wang, H., Zhang, H., Nie, G., Yan, J., & Li, X. (2024) · International Journal of Clinical Practice · doi:10.1155/2024/7081486
“NAFLD in the nonobese population may have a steatosis-like phenotype, characterized by impaired lipogenesis, hypertriglyceridemia, and hepatic steatosis [32].”
BackgroundYamamotoya, T., Ohata, Y., Akasaka, Y., Hasei, S., Inoue, M.-K., Nakatsu, Y., Kanna, M., Yamazaki, H., Kushiyama, A., Fujishiro, M., et al. (2024) · PNAS Nexus · doi:10.1093/pnasnexus/pgae150
“…impaired insulin secretion capacity and insulin resistance, was reported to be prevalent risk factors for this metabolically unhealthy state in normal-weight individuals (7, 9, 10), supporting the significant role of adequate adipose expansion capacity in maintaining a metabolically healthy state.”
Labinska, O., Галькевич, М. П., Луців, Н. З., & Бойків, Н. Д. (2024) · Здобутки клінічної і експериментальної медицини · doi:10.11603/1811-2471.2024.v.i1.14394
Xie, K., Chen, M., An, H., Gao, J., Tang, C., & Huang, Z. (2024) · Therapeutic Advances in Chronic Disease · doi:10.1177/20406223241303649
Minato-Inokawa, S., Honda, M., Tsuboi-Kaji, A., Takeuchi, M., Kitaoka, K., Kurata, M., Wu, B., Kazumi, T., & Fukuo, K. (2023) · Diabetology International · doi:10.1007/s13340-023-00670-w
Total and regional fat-to-muscle mass ratio and risk of incident breast and ovarian cancers
Li, H., Huang, N., Wang, W., Huang, T., & Wang, L. (2023) · Journal of Public Health · doi:10.1007/s10389-023-02116-8
“Although widely used, BMI has certain limitation (Stefan et al. 2017).”
Clinical and thyroid profile in patients with COVID-19 hospitalized in an intensive care unit.
Macías-Gómez, N., Montañez-Valdez, O., Leal-Ugarte, E., Vázquez-Zaragoza, D., & Sigala-Arellano, R. (2023) · European Review for Medical and Pharmacological Sciences · doi:10.26355/eurrev_202309_33591
Nimbhorkar, P. (2023) · International Journal of Science and Research (IJSR) · doi:10.21275/mr23329161839
“In our study, considering the International Obesity Task Force reference for BMI, subjects were divided into obese (≥25) and underweight ( 18) [44] [45].”
Woerkom, A. V., Harney, D. J., Nagarajan, S. R., Hakeem-Sanni, M. F., Lin, J., Hooke, M., Pulpitel, T., Cooney, G., Larance, M., Saunders, D., et al. (2023) · bioRxiv · doi:10.1101/2023.03.09.531813
“Whilst 49 currently there are no universally accepted criteria for identifying metabolically-(un)healthy 50 individuals, generally, it includes a combination of adiposity, insulin sensitivity, inflammation and 51 circulating glucose and lipids [14, 15].”
BackgroundLuo, G., Ai, Y., Yu, L., Wang, S., & Ren, Z. (2023) · Animals · doi:10.3390/ani13030446 · Cited by 1
“With the development of society, obesity has become a more and more serious health problem for contemporary people [22].”
BackgroundGomez-Fernandez-Blanco, C., Peeters, D., Farnir, F., Höglund, K., Gouni, V., Wiberg, M., Willesen, J., Hanås, S., McEntee, K., Tiret, L., et al. (2022) · bioRxiv · doi:10.1101/2022.09.19.508523
Prevalence of coronary risk factors in load transport drivers
Braga, B. B., Ferreira, F. G., Reis, H. H. T., & Marins, J. C. B. (2022) · Revista Brasileira de Medicina do Trabalho · doi:10.47626/1679-4435-2022-695 · Cited by 2
Ist Prädiabetes behandlungsbedürftig?
Stefan, N. (2022) · CardioVasc · doi:10.1007/s15027-022-3669-7
“Da aber auch bei Menschen ohne Adipositas und sogar bei Menschen mit Normalgewicht Stoffwechselerkrankungen auftreten können [18, 19], sind erhöhte Blutzuckerwerte im prädiabetischen Bereich ein einfaches Hilfsmittel, solche Hochrisikopersonen besser zu identifizieren.”
BackgroundSelf-citationAssociation of Obesity with Covid-19 and Nutrition Perspective
Khalid, S., Fida, M., Irfan, H., Arshad, M., Imran, M., Fatima, N., Khalid, M., Javaid, B., Sadiq, K., Rashid, M., et al. (2021) · Lahore Garrison University Journal of Life Sciences · doi:10.54692/lgujls.2021.0504191
Change in Metabolic Health Status Over Time and Risk of Chronic Kidney Disease: A Prospective StudyPreprint
Cui, H., Liu, Q., Wu, Y.-T., & Cao, L. (2021) · Research Square · doi:10.21203/rs.3.rs-1161519/v1
Lisboa, S., Vieira, A., Teodoro, J., Costa, R., Boeno, F., Farinha, J., Reischak-Oliveira, A., Bracht, C., & Cunha, G. D. S. (2021) · Research Square · doi:10.21203/rs.3.rs-653741/v1
Machann, J., Hasenbalg, M., Dienes, J., Wagner, R., Koehn, A., Birkenfeld, A., Nikolaou, K., Kullmann, S., Schick, F., & Heni, M. (2021) · medRxiv · doi:10.1101/2021.06.08.21257560
“5 risk for diabetes, cardiovascular events and mortality (18).”
BackgroundSelf-citationJeong, S., Oh, Y. H., Choi, S., Chang, J., Kim, S. M., Son, J. S., Lee, G., Kim, W. K., & Park, S. M. (2021) · Research Square · doi:10.21203/rs.3.rs-289063/v1
“[6, 7] Currently, ultrasound, vibration-controlled transient elastography, computed tomography, magnetic resonance imaging and spectroscopy, and serum biomarker-based models with available data on the diagnostic and prognostic performances, such as fatty liver index (FLI), are recommended for the detection of HS.”
MethodRelationship Between BMI Degree and Non-Alcoholic Fatty Liver Disease Risk Factors
Marpaung, C. F., Siregar, G. A., & Ilhamd (2021) · Journal of Endocrinology Tropical Medicine and Infectiouse Disease (JETROMI) · doi:10.32734/jetromi.v3i1.5593
“[2] Consequently, this trend entails increased risk of various metabolic disorders, including non-alcoholic fatty liver disease (NAFLD), recently re-named metabolic associated fatty liver disease (MAFLD), which affects about a quarter of the global population.”
BackgroundFettleber und Diabetes: Pathomechanismen
Stefan, N. (2020) · Der Diabetologe · doi:10.1007/s11428-020-00657-0
Self-citationNeue arzneitherapeutische Optionen bei nichtalkoholischer Fettlebererkrankung
Stefan, N. (2020) · Der Internist · doi:10.1007/s00108-020-00801-4 · Cited by 1
“Während diese Zahlen bei adipösen Patienten mit Typ-2-Diabetes noch höher liegen, findet man eine NAFLD auch bei normalgewichtigen Menschen, etwa wenn ein Prädiabetes (11%; [8]) oder eine Kombination von Hyperglykämie, Dyslipidämie und arterieller Hypertonie (19%; [9]) vorliegt.”
BackgroundSelf-citationStefan, N. (2020) · Diabetes Mellitus · doi:10.14341/dm10376 · Cited by 2
Self-citationExploration de la sensibilité à l’insuline chez l’homme : méthodes et indications
Vatier, C., Rabasa-Lhoret, R., Capeau, J., Fève, B., & Bastard, J. (2019) · EMC - Endocrinologie - Nutrition · doi:10.1016/s1155-1941(19)82962-1
Yalçınkaya, E., & Sarıçam, E. (2019) · Ergoterapi ve Rehabilitasyon Dergisi · doi:10.30720/ered.526882
“Obesity is known to be one of the major risk factors of OSA (Stefan, Schick, and Haring 2017; Canoy, Boekholdt, Wareham et al, 2007).”
BackgroundDonnées physiopathologiques et thérapeutiques récentes sur les syndromes lipodystrophiques
Vigouroux, C. (2018) · Médecine des Maladies Métaboliques · doi:10.1016/s1957-2557(18)30173-1
Dissémination du cancer de la prostate : un chemin pavé de gras
Toulet, A. (2018) · theses.fr (ABES) · doi:10.70675/fbbe32c3z7ab7z4857zb7e7z0211baa3fa86
Metabolomic characteristics of fatty pancreas
Jaghutriz, B., Wagner, R., Heni, M., Gerst, F., Siegel-Axel, D., Ullrich, S., Lehmann, R., Machann, J., Stefan, N., Häring, H., et al. (2018) · Diabetologie und Stoffwechsel · doi:10.1055/s-0038-1641787
Self-citationNon-alcoholic Fatty Liver Disease in Non-obese Patients
Schmoyer, C. J., & Siddiqui, M. S. (2017) · Current Hepatology Reports · doi:10.1007/s11901-017-0377-3 · Cited by 1
Metadata
- Authors
- Stefan, N., Schick, F., & Häring, H.-U.
- Affiliations
- Helmholtz Munich (DE)
- Corresponding author
- Stefan, Norbert
- Häring, Hans-Ulrich
- Venue
- Cell Metabolism
- Publisher
- Elsevier BV
- Published
- 2017-08
- Volume
- 26
- Issue
- 2
- Pages
- 292-300
- ISSN
- 1550-4131 (ISSN-L)
- OpenAlex
- W2741982109
- Cited by
- 575
- References
- 0
- Citations by year
- 2026: 50 · 2025: 53 · 2024: 58 · 2023: 60 · 2022: 99 · 2021: 76 · 2020: 88 · 2019: 40 · 2018: 40 · 2017: 10
- FWCI
- 7.10
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Cell Metabolism (publishedVersion)
- PubMed (publishedVersion)
- Site cant be reached (submittedVersion)
- PuSH - Publication Server of Helmholtz Zentrum München (submittedVersion)
- Funders
- Deutsche Forschungsgemeinschaft (KFO 114, STE 1096/1-3)
- Bundesministerium für Bildung und Forschung
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Adipokines, Inflammation, and Metabolic Diseases
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiovascular Disease and Adiposity
- Keywords
- metabolically unhealthy normal weight, metabolic health, cardiometabolic disease, all-cause mortality, cardiovascular risk, adiposity, risk phenotypes, molecular mechanisms, disease prevention, treatment options
- MeSH terms
- Female, Heart Diseases, Humans, Male, Metabolic Diseases, Risk Factors, Body Mass Index, Adiposity
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