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Sindhwani R, Bora KS, Hazra S. The dual challenge of diabesity: pathophysiology, management, and future directions. NAUNYN-SCHMIEDEBERG'S ARCHIVES OF PHARMACOLOGY 2025; 398:4891-4912. [PMID: 39680103 DOI: 10.1007/s00210-024-03713-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/09/2024] [Accepted: 12/07/2024] [Indexed: 12/17/2024]
Abstract
Diabesity, the concurrent occurrence of obesity and type-2 diabetes mellitus (T2DM), represents a pressing global health challenge characterized by intricate pathophysiological mechanisms and a wide range of associated comorbidities. Central to its development are insulin resistance, metabolic syndrome, and chronic low-grade inflammation mediated by dysregulated adipokine secretion and systemic metabolic dysfunction. These mechanisms underpin the progression of diabesity and its complications, including cardiovascular disease and hypertension. Management strategies encompass lifestyle interventions focusing on tailored dietary modifications and structured physical activity, pharmacological treatments targeting both glycemic control and weight loss, and surgical interventions such as bariatric surgery, which have demonstrated efficacy in achieving durable outcomes. Clinical trials and meta-analyses underscore the comparative advantages of different treatment modalities in terms of efficacy, safety, and sustainability. Moreover, long-term follow-up studies emphasize the critical need for sustained multidisciplinary interventions to prevent relapse and enhance patient outcomes. Future advancements in management include exploring precision medicine approaches that integrate individual metabolic profiles, lifestyle factors, and emerging therapeutic innovations. A multidisciplinary approach combining advanced therapeutic strategies and patient-centered care remains pivotal for optimizing management and improving prognoses for individuals with diabesity. This review highlights the complex interplay between obesity and T2DM, offering comprehensive insights into their pathophysiology, clinical presentation, and management paradigms.
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Affiliation(s)
- Ritika Sindhwani
- University Institute of Pharma Sciences, Chandigarh University, Mohali, 140413, Punjab, India
| | - Kundan Singh Bora
- University Institute of Pharma Sciences, Chandigarh University, Mohali, 140413, Punjab, India.
| | - Subhajit Hazra
- University Institute of Pharma Sciences, Chandigarh University, Mohali, 140413, Punjab, India
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Carbayo-Herencia JA, Simarro Rueda M, Artigao Ródenas LM, Divisón Garrote JA, Molina Escribano F, Ponce García I, Palazón Bru A, Torres Moreno P, Caldevilla Bernardo D, Martínez López R, Gil Guillén VF, Banegas JR. Diabesity and cardiovascular mortality in a prospective population cohort followed for more than 20 years. CLINICA E INVESTIGACION EN ARTERIOSCLEROSIS : PUBLICACION OFICIAL DE LA SOCIEDAD ESPANOLA DE ARTERIOSCLEROSIS 2025:500768. [PMID: 39955205 DOI: 10.1016/j.arteri.2025.500768] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/30/2024] [Revised: 01/20/2025] [Accepted: 01/20/2025] [Indexed: 02/17/2025]
Abstract
INTRODUCTION Control of the main cardiovascular risk factors had succeeded in reducing cardiovascular diseases (CVD). However, the general increase in the prevalence of type 2 diabetes mellitus (DM2) and obesity has slowed this decline. Both CVRFs are strongly associated, and the term diabesity has been coined to refer to this relationship. The main objective of this study was to assess the influence of diabesity on cardiovascular mortality. METHODS Prospective cohort study involving 1246 individuals (54.3% women) followed for 20.9 years (SD=7.31) and selected by random two-stage sampling in a province in southeastern Spain. Diabesity was defined as the combination of DM2 with overweight and obesity. Survival curves (Kaplan-Meier) were calculated and two Cox regression models were used, one unadjusted and the other adjusted by the main explanatory variables in which the diabesity variable consisted of 6 categories (normal weight, overweight, obesity, normal weight+DM2, overweight+DM2 and obesity+DM2). RESULTS There were 95 deaths due to CV causes (7.6% of the total; 6.2% women and 9.3% men; p=0.01). After adjustment, the combination of DM2 and overweight increased the incidence of cardiovascular mortality by 133% (HR=2.33; 95% CI: 1.18-4.58; p=0.014) and the combination of DM2 and obesity by 49% (HR=1.49; 95% CI: 0.64-3.45; p=0.351), not reaching statistical significance in the latter case. CONCLUSIONS In the general population, the results of our study show that the combination of overweight and DM2 is associated with higher CV mortality. It seems a priority to intervene intensively in the control of both overweight and DM2.
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Affiliation(s)
- Julio A Carbayo-Herencia
- Departamento de Medicina Clínica, Universidad Miguel Hernández, San Juan de Alicante, España; Grupo de Enfermedades Vasculares de Albacete (GEVA).
| | - Marta Simarro Rueda
- Centro de Salud de Chinchilla, Albacete, España; Grupo de Enfermedades Vasculares de Albacete (GEVA)
| | | | - Juan A Divisón Garrote
- Facultad de Medicina, Universidad Católica San Antonio Murcia (UCAM), Murcia, España; Grupo de Enfermedades Vasculares de Albacete (GEVA)
| | | | - Isabel Ponce García
- Centro de Salud de Tarazona de la Mancha, Albacete, España; Grupo de Enfermedades Vasculares de Albacete (GEVA)
| | | | - Pilar Torres Moreno
- Centro de Salud de Alcadozo, Albacete, España; Grupo de Enfermedades Vasculares de Albacete (GEVA)
| | - David Caldevilla Bernardo
- Servicio de Radiodiagnóstico, Complejo Hospitalario Universitario de Albacete, Universidad de Castilla-La Mancha, Albacete, España; Grupo de Enfermedades Vasculares de Albacete (GEVA)
| | - Rosalina Martínez López
- Servicio de Análisis Clínicos (Bioquímica clínica), Complejo Hospitalario y Universitario de Albacete (CHUA), Albacete, España; Grupo de Enfermedades Vasculares de Albacete (GEVA)
| | - Vicente Francisco Gil Guillén
- Departamento de Medicina Clínica, Universidad Miguel Hernández, San Juan de Alicante, España; Grupo de Enfermedades Vasculares de Albacete (GEVA)
| | - José R Banegas
- Departamento de Medicina Preventiva y Salud Pública, Universidad Autónoma de Madrid y CIBERESP, Madrid, España; Grupo de Enfermedades Vasculares de Albacete (GEVA)
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Petermann-Rocha F, Apolinar E, Nazar G, Diaz-Toro F, Celis A, Deo S, Ferrari G, O'Donovan G. Associations of diabesity with all-cause and cardiovascular disease mortality: Findings from the Mexico City Prospective Study. Diabetes Obes Metab 2024; 26:2199-2208. [PMID: 38439662 DOI: 10.1111/dom.15528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Revised: 02/12/2024] [Accepted: 02/14/2024] [Indexed: 03/06/2024]
Abstract
AIM To investigate the joint associations of diabetes and obesity with all-cause and cardiovascular disease (CVD) mortality in the Mexico City Prospective Study. MATERIALS AND METHODS In total, 154 128 participants (67.2% women) were included in this prospective analysis. Diabetes was self-reported, while body mass index was used to calculate obesity. Using diabetes and obesity classifications, six groups were created: (a) normal (no diabetes and normal weight); (b) normal weight and diabetes; (c) overweight but not diabetes (overweight); (d) overweight and diabetes (prediabesity); (e) obesity but not diabetes (obesity); and (f) obesity and diabetes (diabesity). Associations between these categories and outcomes were investigated using Cox proportional hazard models adjusted for confounder factors. RESULTS During 18.3 years of follow-up, 27 197 (17.6%) participants died (28.5% because of CV causes). In the maximally adjusted model, participants those with the highest risk {hazard ratio (HR): 2.37 [95% confidence interval (CI): 2.24-2.51]}, followed by those with diabesity [HR: 2.04 (95% CI: 1.94-2.15)]. Similar trends of associations were observed for CVD mortality. The highest CV mortality risk was observed in individuals with diabesity [HR: 1.80 (95% CI: 1.63-1.99)], followed by normal weight and diabetic individuals [HR: 1.78 (95% CI: 1.60-1.98)]. CONCLUSION This large prospective study identified that diabetes was the main driver of all-cause and CVD mortality in all the categories studied, with diabesity being the riskiest. Given the high prevalence of both conditions in Mexico, our results reinforce the importance of initiating prevention strategies from an early age.
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Affiliation(s)
- Fanny Petermann-Rocha
- Centro de Investigación Biomédica, Facultad de Medicina, Universidad Diego Portales, Santiago, Chile
- School of Cardiovascular and Metabolic Health, University of Glasgow, Glasgow, UK
| | - Evelia Apolinar
- Unidad de Metabolismo y Nutrición, Departamento de Investigación, Hospital Regional de Alta Especialidad del Bajío, Secretaría de Salud, León, Mexico
| | - Gabriela Nazar
- Departamento de Psicología, Universidad de Concepción, Concepción, Chile
- Centro de Vida Saludable, Universidad de Concepción, Concepción, Chile
| | - Felipe Diaz-Toro
- Facultad de Enfermeria, Universidad Andrés Bello, Santiago, Chile
| | - Andrés Celis
- Facultad de Odontología, Universidad de los Andes, Santiago, Chile
| | - Salil Deo
- Louis Stokes Cleveland VA Medical Center, Cleveland, Ohio, USA
- Case School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA
- School of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Gerson Ferrari
- Escuela de Ciencias de la Actividad Física, el Deporte y la Salud, Universidad de Santiago de Chile (USACH), Santiago, Chile
- Facultad de Ciencias de la Salud, Universidad Autónoma de Chile, Santiago, Chile
| | - Gary O'Donovan
- Facultad de Medicina, Universidad de los Andes, Bogotá, Colombia
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
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Li C, Peng Y, Zhu X, Liu Y, Zou J, Zhu H, Li X, Yi H, Guan J, Zhang X, Xu H, Yin S. Independent relationship between sleep apnea-specific hypoxic burden and glucolipid metabolism disorder: a cross-sectional study. Respir Res 2024; 25:214. [PMID: 38762509 PMCID: PMC11102635 DOI: 10.1186/s12931-024-02846-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Accepted: 05/12/2024] [Indexed: 05/20/2024] Open
Abstract
OBJECTIVES Obstructive sleep apnea (OSA) is associated with abnormal glucose and lipid metabolism. However, whether there is an independent association between Sleep Apnea-Specific Hypoxic Burden (SASHB) and glycolipid metabolism disorders in patients with OSA is unknown. METHODS We enrolled 2,173 participants with suspected OSA from January 2019 to July 2023 in this study. Polysomnographic variables, biochemical indicators, and physical measurements were collected from each participant. Multiple linear regression analyses were used to evaluate independent associations between SASHB, AHI, CT90 and glucose as well as lipid profile. Furthermore, logistic regressions were used to determine the odds ratios (ORs) for abnormal glucose and lipid metabolism across various SASHB, AHI, CT90 quartiles. RESULTS The SASHB was independently associated with fasting blood glucose (FBG) (β = 0.058, P = 0.016), fasting insulin (FIN) (β = 0.073, P < 0.001), homeostasis model assessment of insulin resistance (HOMA-IR) (β = 0.058, P = 0.011), total cholesterol (TC) (β = 0.100, P < 0.001), total triglycerides (TG) (β = 0.063, P = 0.011), low-density lipoprotein cholesterol (LDL-C) (β = 0.075, P = 0.003), apolipoprotein A-I (apoA-I) (β = 0.051, P = 0.049), apolipoprotein B (apoB) (β = 0.136, P < 0.001), apolipoprotein E (apoE) (β = 0.088, P < 0.001) after adjustments for confounding factors. Furthermore, the ORs for hyperinsulinemia across the higher SASHB quartiles were 1.527, 1.545, and 2.024 respectively, compared with the lowest quartile (P < 0.001 for a linear trend); the ORs for hyper-total cholesterolemia across the higher SASHB quartiles were 1.762, 1.998, and 2.708, compared with the lowest quartile (P < 0.001 for a linear trend) and the ORs for hyper-LDL cholesterolemia across the higher SASHB quartiles were 1.663, 1.695, and 2.316, compared with the lowest quartile (P < 0.001 for a linear trend). Notably, the ORs for hyper-triglyceridemia{1.471, 1.773, 2.099} and abnormal HOMA-IR{1.510, 1.492, 1.937} maintained a consistent trend across the SASHB quartiles. CONCLUSIONS We found SASHB was independently associated with hyperinsulinemia, abnormal HOMA-IR, hyper-total cholesterolemia, hyper-triglyceridemia and hyper-LDL cholesterolemia in Chinese Han population. Further prospective studies are needed to confirm that SASHB can be used as a predictor of abnormal glycolipid metabolism disorders in patients with OSA. TRIAL REGISTRATION ChiCTR1900025714 { http://www.chictr.org.cn/ }; Prospectively registered on 6 September 2019; China.
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Affiliation(s)
- Chenyang Li
- Department of Otolaryngology-Head and Neck Surgery & Center of Sleep Medicine, Shanghai Jiao Tong University School of Medicine Affiliated Sixth People's Hospital, Shanghai, China
- Shanghai Key Laboratory of Sleep Disordered Breathing, Shanghai, China
| | - Yu Peng
- Department of Otolaryngology-Head and Neck Surgery & Center of Sleep Medicine, Shanghai Jiao Tong University School of Medicine Affiliated Sixth People's Hospital, Shanghai, China
- Shanghai Key Laboratory of Sleep Disordered Breathing, Shanghai, China
| | - Xiaoyue Zhu
- Department of Otolaryngology-Head and Neck Surgery & Center of Sleep Medicine, Shanghai Jiao Tong University School of Medicine Affiliated Sixth People's Hospital, Shanghai, China
- Shanghai Key Laboratory of Sleep Disordered Breathing, Shanghai, China
| | - Yupu Liu
- Department of Otolaryngology-Head and Neck Surgery & Center of Sleep Medicine, Shanghai Jiao Tong University School of Medicine Affiliated Sixth People's Hospital, Shanghai, China
- Shanghai Key Laboratory of Sleep Disordered Breathing, Shanghai, China
| | - Jianyin Zou
- Department of Otolaryngology-Head and Neck Surgery & Center of Sleep Medicine, Shanghai Jiao Tong University School of Medicine Affiliated Sixth People's Hospital, Shanghai, China
- Shanghai Key Laboratory of Sleep Disordered Breathing, Shanghai, China
| | - Huaming Zhu
- Department of Otolaryngology-Head and Neck Surgery & Center of Sleep Medicine, Shanghai Jiao Tong University School of Medicine Affiliated Sixth People's Hospital, Shanghai, China
- Shanghai Key Laboratory of Sleep Disordered Breathing, Shanghai, China
| | - Xinyi Li
- Department of Otolaryngology-Head and Neck Surgery & Center of Sleep Medicine, Shanghai Jiao Tong University School of Medicine Affiliated Sixth People's Hospital, Shanghai, China
- Shanghai Key Laboratory of Sleep Disordered Breathing, Shanghai, China
| | - Hongliang Yi
- Department of Otolaryngology-Head and Neck Surgery & Center of Sleep Medicine, Shanghai Jiao Tong University School of Medicine Affiliated Sixth People's Hospital, Shanghai, China
- Shanghai Key Laboratory of Sleep Disordered Breathing, Shanghai, China
| | - Jian Guan
- Department of Otolaryngology-Head and Neck Surgery & Center of Sleep Medicine, Shanghai Jiao Tong University School of Medicine Affiliated Sixth People's Hospital, Shanghai, China.
- Shanghai Key Laboratory of Sleep Disordered Breathing, Shanghai, China.
| | - Xu Zhang
- School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen, China.
| | - Huajun Xu
- Department of Otolaryngology-Head and Neck Surgery & Center of Sleep Medicine, Shanghai Jiao Tong University School of Medicine Affiliated Sixth People's Hospital, Shanghai, China.
- Shanghai Key Laboratory of Sleep Disordered Breathing, Shanghai, China.
| | - Shankai Yin
- Department of Otolaryngology-Head and Neck Surgery & Center of Sleep Medicine, Shanghai Jiao Tong University School of Medicine Affiliated Sixth People's Hospital, Shanghai, China
- Shanghai Key Laboratory of Sleep Disordered Breathing, Shanghai, China
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