Publication:
High-Risk Obesity Phenotypes: Target for Multimorbidity Prevention at the ROFEMI Study.

Loading...
Thumbnail Image

Date

2022-08-02

Authors

Carretero-Gomez, Juana
Perez-Martinez, Pablo
Segui-Ripoll, Jose Miguel
Carrasco-Sanchez, Francisco Javier
Lois Martinez, Nagore
Fernandez Perez, Esther
Perez Hernandez, Onan
Garcia Ordoñez, Miguel Angel
Martin Gonzalez, Candelaria
Vigueras-Perez, Juan Francisco

Advisors

Journal Title

Journal ISSN

Volume Title

Publisher

MDPI
Metrics
Google Scholar
Export

Research Projects

Organizational Units

Journal Issue

Abstract

Background: Describe the profile of patients with obesity in internal medicine to determine the role of adiposity and related inflammation on the metabolic risk profile and, identify various “high-risk obesity” phenotypes by means of a cluster analysis. This study aimed to identify different profiles of patients with high-risk obesity based on a cluster analysis. Methods: Cross-sectional, multicenter project that included outpatients attended to in internal medicine. A total of 536 patients were studied. The mean age was 62 years, 51% were women. Patients were recruited from internal medicine departments over two weeks in November and December 2021 and classified into four risk groups according to body mass index (BMI) and waist circumference (WC). High-risk obesity was defined as BMI > 35 Kg/m2 or BMI 30−34.9 Kg/m2 and a high WC (>102 cm for men and >88 cm for women). Hierarchical and partitioning clustering approaches were performed to identify profiles. Results: A total of 462 (86%) subjects were classified into the high-risk obesity group. After excluding 19 patients missing critical data, two profiles emerged: cluster 1 (n = 396) and cluster 2 (n = 47). Compared to cluster 1, cluster 2 had a worse profile, characterized by older age (77 ± 16 vs. 61 ± 21 years, p 35 Kg/m2 or BMI 30−34.9 Kg/m2 and a high WC (>102 cm for men and >88 cm for women). Hierarchical and partitioning clustering approaches were performed to identify profiles. Results: A total of 462 (86%) subjects were classified into the high-risk obesity group. After excluding 19 patients missing critical data, two profiles emerged: cluster 1 (n = 396) and cluster 2 (n = 47). Compared to cluster 1, cluster 2 had a worse profile, characterized by older age (77 ± 16 vs. 61 ± 21 years, p 102 cm for men and >88 cm for women). Hierarchical and partitioning clustering approaches were performed to identify profiles. Results: A total of 462 (86%) subjects were classified into the high-risk obesity group. After excluding 19 patients missing critical data, two profiles emerged: cluster 1 (n = 396) and cluster 2 (n = 47). Compared to cluster 1, cluster 2 had a worse profile, characterized by older age (77 ± 16 vs. 61 ± 21 years, p 88 cm for women). Hierarchical and partitioning clustering approaches were performed to identify profiles. Results: A total of 462 (86%) subjects were classified into the high-risk obesity group. After excluding 19 patients missing critical data, two profiles emerged: cluster 1 (n = 396) and cluster 2 (n = 47). Compared to cluster 1, cluster 2 had a worse profile, characterized by older age (77 ± 16 vs. 61 ± 21 years, p 3 (53% vs. 5%, p< 0.001), depression (36% vs. 19%, p = 0.008), severe disability (64% vs. 3%, p < 0.001), and a sarcopenia score ≥ 4 (79% vs. 16%, p < 0.01). In addition, cluster 2 had greater inflammation than cluster 1 (hsCRP: 5.8 ± 4.1 vs. 2.1 ± 4.5 mg/dL, p = 0.008). Conclusions: Two profiles of subjects with high-risk obesity were identified. Based on that, older subjects with obesity require measures that target sarcopenia, disability, psychological health, and significant comorbidities to prevent further health deterioration. Longitudinal studies should be performed to identify potential risk factors of subjects who progress from cluster 1 to cluster 2.

Description

MeSH Terms

Middle Aged
Body Mass Index
C-Reactive Protein
Adiposity
Outpatients
Sarcopenia
Depression

DeCS Terms

Adiposidad
Depresión
Pacientes ambulatorios
Proteína C-reactiva
Índice de masa corporal

CIE Terms

Keywords

Adiposity, Inflammation, Obesity, Phenotypes, Waist circumference, Área de Gestión Sanitaria Norte de Málaga

Citation

Carretero-Gómez J, Pérez-Martínez P, Seguí-Ripoll JM, Carrasco-Sánchez FJ, Lois Martínez N, Fernández Pérez E, et al. High-Risk Obesity Phenotypes: Target for Multimorbidity Prevention at the ROFEMI Study. J Clin Med. 2022 Aug 9;11(16):4644