Umeh K, Adaji S
School of Psychology, Faculty of Health, Liverpool John Moores University, Liverpool, Merseyside, L3 3AF, UK.
Sessional General Practitioner, Bousfield Health Centre, Westminster Road, Liverpool, L4 4PP, UK.
BMC Prim Care. 2025 May 16;26(1):171. doi: 10.1186/s12875-024-02671-3.
Although most of the management of type 2 diabetes (T2DM) occurs in primary care, and physicians are tasked with using a 'whole person' approach, there is currently a lack of research on psychosocial diagnostic indicators for detecting metabolic abnormalities in T2DM patients. This study examined relations between SRH and metabolic abnormalities in patients with type 2 diabetes, adjusting for metabolic comorbidity.
A total of 583 adults with type 2 diabetes were identified from the 2019 HSE (Health Survey for England). Data on metabolic syndrome (MetS) was extracted, including lipids (high density lipoprotein cholesterol (HDL-C)), glycated haemoglobin (HbA1c), blood pressure (systolic/diastolic), and anthropometric measures (BMI, waist/hip ratio). Bootstrapped hierarchical regression and structural equation modelling (SEM) were used to analyse the data.
Adjusting for metabolic covariates attenuated significant associations between SRH and metabolic abnormalities (HDL-C, HbA1c), regardless of MetS status. Analysis by gender uncovered covariate-adjusted associations between SRH and both HDL-C (in men) and HbA1c (in women) (p's = 0.01), albeit these associations were no longer significant when evaluated against a Bonferroni-adjusted alpha value (p > 0.004). Sensitivity analysis indicated most findings were unaffected by the type of algorithm used to manage missing data. SEM revealed no indirect associations between SRH, metabolic abnormalities, and lifestyle factors.
While poor SRH can help primary care physicians identify T2DM patients with metabolic dysfunction, it may not offer added diagnostic usefulness over clinical biomarkers.
尽管2型糖尿病（T2DM）的大部分管理工作在初级保健中进行，且医生的任务是采用“全人”方法，但目前缺乏关于检测T2DM患者代谢异常的社会心理诊断指标的研究。本研究在调整代谢合并症的情况下，考察了2型糖尿病患者的健康自评（SRH）与代谢异常之间的关系。
从2019年英国健康调查（HSE）中识别出583名2型糖尿病成年患者。提取了代谢综合征（MetS）的数据，包括血脂（高密度脂蛋白胆固醇（HDL-C））、糖化血红蛋白（HbA1c）、血压（收缩压/舒张压）和人体测量指标（体重指数（BMI）、腰臀比）。采用自抽样分层回归和结构方程模型（SEM）对数据进行分析。
无论MetS状态如何，调整代谢协变量后，SRH与代谢异常（HDL-C、HbA1c）之间的显著关联减弱。按性别分析发现，SRH与HDL-C（男性）和HbA1c（女性）之间存在协变量调整后的关联（p值均为0.01），尽管根据Bonferroni校正的α值评估时这些关联不再显著（p>0.004）。敏感性分析表明，大多数结果不受用于处理缺失数据的算法类型的影响。SEM显示，SRH、代谢异常和生活方式因素之间不存在间接关联。
虽然健康自评较差有助于初级保健医生识别有代谢功能障碍的T2DM患者，但与临床生物标志物相比，它可能并没有额外的诊断价值。
