As diabetes-related multimorbidity becomes increasingly prevalent, patients face growing demands associated with treatment and self-management. However, quantitative evidence on burden patterns and high-risk population characteristics in primary health care settings in China remains limited.

To assess management burden among middle-aged and older adults with diabetes and multimorbidity in primary health care settings from a patient-experience perspective, to identify latent burden subtypes, and to examine the sociodemographic characteristics associated with different burden profiles, thereby informing targeted identification of high-burden patients in primary care.

Data were drawn from the Multimorbidity Burden and Primary Health Care Research in China (MBPC) project. A cross-sectional survey was conducted between August and December 2023 in six primary health care institutions across three provinces in China (Shandong, Fujian, and Guangxi). A total of 248 patients aged ≥45 years with diabetes and at least one additional chronic condition were included. Management burden was assessed using the Chinese version of the Patient Experience with Treatment and Self-management (PETS 2.0), covering 14 dimensions. Latent profile analysis (LPA) was applied to identify burden subtypes, and multinomial Logistic regression was used to examine factors associated with different subtypes.

The mean age of participants was (69.6±10.1) years, and 61.3% (152/248) had three or more comorbid conditions. Overall management burden was substantial, with the highest scores observed in dietary management (45.9), exercise or physical therapy (42.5), access to health care services (42.4), medical and health care costs (37.8), and access to medical information (31.5). LPA identified three distinct burden subtypes: low overall burden (53, 21.37%), balanced moderate burden (170, 68.55%), and multidimensional high burden (25, 10.08%). Compared with patients in the balanced moderate-burden and low-burden groups, those in the multidimensional high-burden group were more likely to report difficulties in scheduling specialist appointments, arranging suitable appointment times, coping with long waiting times for consultations, affording medical-related expenses, and understanding medication-related information (all P<0.05). Multinomial Logistic regression showed that increasing age was associated with a higher likelihood of belonging to the high-burden group (RRR=1.098, P=0.008), whereas higher educational attainment (RRR=0.159, P=0.008) and higher income level (RRR=0.231, P=0.034) were associated with a lower likelihood.

Management burden among middle-aged and older adults with diabetes and multimorbidity exhibits a clear stratified structure and is primarily driven by system-related management demands, including information processing, care coordination, and financial management. Older adults and individuals with lower education and income are more likely to experience multidimensional high burden. Primary care management should move beyond routine disease control to prioritize the identification of high-burden patients and implement targeted interventions focusing on information support, process simplification, and continuity of care.

随着糖尿病共病日益普遍，患者治疗与自我管理负担不断增加，但我国基层卫生服务情境下相关负担模式及高风险人群特征尚缺少量化证据。

基于患者体验视角，测量基层卫生服务情境下中老年糖尿病共病患者的治疗负担水平，识别其潜在亚型结构，并分析不同负担亚型的人群特征，为基层精准识别高负担患者提供依据。

基于"中国慢性病共病负担与基本卫生保健研究（MBPC）"数据，2023年8—12月在山东省、福建省、广西壮族自治区6所基层医疗卫生机构开展横断面调查。纳入年龄≥45岁且合并≥1种慢性病的糖尿病患者248例。采用中文版患者治疗与自我管理体验量表（PETS 2.0量表）评估14个维度的治疗负担。通过潜在剖面分析（LPA）识别负担亚型，并采用多分类Logistic回归分析不同亚型的相关因素。

糖尿病共病患者的平均年龄为（69.6±10.1）岁，共病数≥3种者占61.3%（152/248）。总体治疗负担较高，主要集中在饮食控制（45.9分）、运动或物理治疗（42.5分）、医疗服务获取（42.4分）、医疗与健康保健费用（37.8分）及医疗信息获取（31.5分）等方面。LPA识别出3类负担亚型：低整体负担型（53例，21.37%）、均衡中等负担型（170例，68.55%），多维高负担型（25例，10.08%）。与均衡中等负担型和低整体负担型相比，多维高负担型患者"专科门诊难以预约""难以预约合适就诊时间""就诊等待时间过长""难以负担医疗相关费用"及"理解药物信息困难"等问题比例均更高（P<0.05）。多分类Logistic回归结果显示，年龄增加与进入多维高负担型风险升高相关（RRR=1.098，P=0.008），而较高教育水平（RRR=0.159，P=0.008）及较高收入水平（RRR=0.231，P=0.034）与较低风险相关。

中老年糖尿病共病患者的治疗负担呈现明显分层结构，主要由信息处理、就诊协调及费用管理等系统性管理负担所驱动。高龄、受教育程度低及低收入人群更易进入多维高负担状态。基层慢性病管理应在常规疾病控制基础上，加强对高负担风险患者的识别，并围绕信息支持、流程简化及连续照护开展针对性干预。