Vera-Ponce Víctor Juan, Zuzunaga-Montoya Fiorella E, Vásquez-Romero Luisa Erika Milagros, Loayza-Castro Joan A, Iturregui Paucar Cori Raquel, Vigil-Ventura Enrique, Gutiérrez De Carrillo Carmen Inés
Instituto de Investigación de Enfermedades Tropicales, Universidad Nacional Toribio Rodríguez de Mendoza de Amazonas (UNTRM), Amazonas, Perú.
Facultad de Medicina (FAMED), Universidad Nacional Toribio Rodríguez de Mendoza de Amazonas (UNTRM), Amazonas, Perú.
Diabetol Metab Syndr. 2024 Aug 1;16(1):186. doi: 10.1186/s13098-024-01411-y.
Although obesity substantially influences public health owing to related comorbidities, it has been discovered that the incidence of such issues is not directly related to obesity but to the patient's unhealthy metabolic status (MUS) independent of the body mass index (BMI).
To describe the prevalence of UMS overall and according to BMI and determine the factors associated with it.
A cross-sectional analytical study was used based on the analysis of secondary databases called the Life Stage Nutritional Surveillance Survey (VIANEV). Participants were selected in two stages, finally obtaining 885 participants. UMS was defined based on the criteria of the Adult Treatment Panel III used to define metabolic status in a set of 5 parameters, if the subject presented two or more alterations it was considered UMS. Six groups were formed according to BMI: metabolically healthy, average weight (MHNW) and unhealthy (MUNW), metabolically healthy, overweight (MHOW) and unhealthy (MUOW), metabolically healthy, obese (MHO) and unhealthy (MUO).).
The total prevalence of UMS was 73.11%, with MUNW, MUOW, and MUO being 47.90%, 80.34%, and 96.44%, respectively. Only 5.31% did not present any metabolic alteration. The multivariable analysis found variations globally according to sex, age, marital status, geographical region, smoking habit, and altitude.
A high prevalence of UMS was observed in Peru, indicating that BMI alone is not a sufficient indicator of metabolic status. These findings suggest that strategies should be prioritized to address the growing problem of UMS, considering the particularities of each subpopulation and using a multifaceted approach that addresses modifiable and non-modifiable risk factors.
尽管肥胖因其相关合并症对公众健康有重大影响，但已发现此类问题的发生率并非直接与肥胖相关，而是与患者独立于体重指数（BMI）的不健康代谢状态（MUS）有关。
描述总体及按BMI划分的不健康代谢状态（UMS）的患病率，并确定与之相关的因素。
采用横断面分析研究，基于对名为生命阶段营养监测调查（VIANEV）的二次数据库进行分析。参与者分两个阶段选取，最终获得885名参与者。UMS根据用于定义一组5个参数代谢状态的成人治疗小组III标准来定义，如果受试者出现两个或更多改变，则被视为UMS。根据BMI分为六组：代谢健康、体重正常（MHNW）和不健康（MUNW），代谢健康、超重（MHOW）和不健康（MUOW），代谢健康、肥胖（MHO）和不健康（MUO）。
UMS的总患病率为73.11%，其中MUNW、MUOW和MUO分别为47.90%、80.34%和96.44%。只有5.31%的人未出现任何代谢改变。多变量分析发现，总体上根据性别、年龄、婚姻状况、地理区域、吸烟习惯和海拔存在差异。
在秘鲁观察到UMS的高患病率，表明仅BMI不足以作为代谢状态的指标。这些发现表明，应优先考虑采取策略来解决日益严重的UMS问题，考虑每个亚人群的特殊性，并采用多方面方法来解决可改变和不可改变的风险因素。
