Zeng Lin, Zhang Yan-Ping, Zhang Xin, Chen Jing-Feng, Bai Chao-Qun, Lei Xiao-Xue, Fu Gui-Fen
Department of Geriatric Endocrinology and Metabolism, Guangxi Academy of Medical Sciences and the People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China.
Department of Geriatric Endocrinology and Metabolism, People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China.
BMJ Open. 2025 Jan 21;15(1):e088891. doi: 10.1136/bmjopen-2024-088891.
The purpose of this study was to analyse the heterogeneity of health information-seeking behaviour (HISB) among patients with type 2 diabetes (T2D) in rural areas based on latent profiles and to explore the relationship between various behaviours and glycaemic control rates and the factors influencing glycaemic control rates.
Between January and July 2022, a stratified cluster random sampling method was used to sample T2D patients in the rural Guangxi Zhuang Autonomous Region. Participants completed a general information questionnaire and a HISB scale. Latent profile analysis (LPA) identified behaviour categories, and χ tests examined differences in glycaemic control rates across these categories. Multivariate logistic regression was used to analyse factors influencing glycaemic control. The glycaemic control rate was defined as the proportion of individuals whose HbA1c levels are less than 7.0%, indicating good control, in relation to the total number of individuals assessed.
A total of 2178 valid questionnaires were received in this study, and respondents were divided into three categories according to the LPA of their HISB: negative (18.3%), occlusive (46.8%) and inefficient (34.9%). The glycaemic control rate of patients with T2D in rural areas was 22.6% (494/2178 cases). Multivariate logistic regression analysis revealed that the category of patients' HISB profile, age, course of disease and educational level were the factors influencing the glycaemic control rate (all p<0.05).
Patients with T2D in rural areas had poor glycaemic control and inadequate HISB. Three latent profile categories were identified that reflect the HISB of this group. We recommend that clinical medical professionals develop personalised health management education based on the various latent profile characteristics of patients to promote HISB and thereby achieve optimal glycaemic control.
本研究旨在基于潜在类别分析农村地区2型糖尿病（T2D）患者健康信息寻求行为（HISB）的异质性，并探讨各种行为与血糖控制率之间的关系以及影响血糖控制率的因素。
2022年1月至7月，采用分层整群随机抽样方法对广西壮族自治区农村地区的T2D患者进行抽样。参与者完成了一份一般信息问卷和一份HISB量表。潜在类别分析（LPA）确定行为类别，χ检验检查这些类别之间血糖控制率的差异。多因素logistic回归用于分析影响血糖控制的因素。血糖控制率定义为糖化血红蛋白（HbA1c）水平低于7.0%（表明控制良好）的个体数量占评估个体总数的比例。
本研究共收到2178份有效问卷，根据HISB的LPA将受访者分为三类：消极型（18.3%）、封闭型（46.8%）和低效型（34.9%）。农村地区T2D患者的血糖控制率为22.6%（494/2178例）。多因素logistic回归分析显示，患者HISB概况类别、年龄、病程和教育水平是影响血糖控制率的因素（均p<0.05）。
农村地区T2D患者血糖控制不佳且HISB不足。确定了三个潜在类别，反映了该群体的HISB。我们建议临床医疗专业人员根据患者的各种潜在类别特征开展个性化的健康管理教育，以促进HISB，从而实现最佳血糖控制。
