摘要目的:估算我国成年人2型糖尿病发病率，比较不同数据源对发病率估算的影响并分析这种差异在不同特征人群中的一致性。方法:基于中国慢性病前瞻性研究（CKB）中参加第二次（2013年8月至2014年9月， n=23 438）和第三次（2020年8月至2021年12月， n=23 326）重复调查的人群，通过现场调查（结合问卷自报和血糖检测）、问卷自报及随访监测（链接多源数据库）方式，分别确定随访期间新诊断的2型糖尿病病例。采用直接标准化法计算年龄标化发病率，并用广义线性混合效应模型估算现场调查与随访监测确定的糖尿病发病率比（ IRR）及95% CI。 结果:在第二次重复调查人群中，现场调查、问卷自报及随访监测数据估算的2型糖尿病粗发病率（/1 000人年）分别为8.4（95% CI：7.9~8.9）、4.3（95% CI：3.9~4.6）和2.8（95% CI：2.5~3.1），第三次重复调查人群中的对应粗发病率（/1 000人年）为8.3（95% CI：7.9~8.6）、6.2（95% CI：5.9~6.5）和5.8（95% CI：5.5~6.1）。2组人群经现场调查确定的年龄标化发病率（/1 000人年）分别为7.6（95% CI：7.1~8.2）和7.4（95% CI：7.0~7.8）。在第二次重复调查人群中，现场调查与随访监测确定的2型糖尿病 IRR为3.27（95% CI：2.90~3.70）；第三次重复调查人群中， IRR下降至1.46（95% CI：1.37~1.56），且该趋势在不同特征人群中均有所体现。2次调查人群均显示，文化程度为中学及以上者、家庭年收入<20 000元者、中心性肥胖者、未患冠心病或脑血管病者，其 IRR相对更高，即相比现场调查，随访监测对发病率的低估更为明显。 结论:本研究发现，在大型人群队列研究随访过程中，相较于单一数据源，整合多源医疗健康大数据可显著提升2型糖尿病新发病例识别的全面性和及时性。

abstractsObjective:To estimate the incidence of type 2 diabetes among adults in China, evaluate the influence of data from different sources on incidence estimation, and analyze the consistency of such differences across population subgroups.Methods:Based on participants in the second (August 2013 to September 2014, n=23 438) and third (August 2020 to December 2021, n=23 326) resurveys of the China Kadoorie Biobank, new-onset type 2 diabetes cases during follow-up were identified separately through three approaches: field survey (combining questionnaire-based self-report and blood glucose testing), questionnaire-based self-report, and follow-up monitoring through linkage to multiple healthcare databases. Age-standardized incidence rates were calculated using the direct standardization method. Generalized linear mixed-effects models were used to estimate incidence rate ratios ( IRRs) and 95% CIs comparing incidence ascertained through field survey versus follow-up monitoring. Results:Among participants in the second resurvey, the crude incidence rates (/1 000 person-years) estimated using field survey, questionnaire-based self-report, and follow-up monitoring were 8.4 (95% CI: 7.9-8.9), 4.3 (95% CI: 3.9-4.6), and 2.8 (95% CI: 2.5-3.1), respectively. The corresponding crude incidence rates(/1 000 person-years) in the third resurvey were 8.3 (95% CI: 7.9-8.6), 6.2 (95% CI: 5.9-6.5), and 5.8 (95% CI:5.5-6.1), respectively. The age-standardized incidence rate (/1 000 person-years) was 7.6 (95% CI: 7.1-8.2) in the second resurvey and 7.4 (95% CI:7.0-7.8) in the third resurvey based on field survey results. The IRR comparing field survey with follow-up monitoring was 3.27 (95% CI: 2.90-3.70) in the second resurvey and declined to 1.46 (95% CI: 1.37-1.56) in the third resurvey, with this trend being observed consistently across subgroups. In both resurveys, participants with an education level of middle school or above, those with annual household income <20 000 Yuan, those with central obesity, and those without coronary heart disease or stroke showed relatively higher IRRs, indicating that incidence was more markedly underestimated by follow-up monitoring in these subgroups compared with field survey. Conclusion:This study indicated that in large population-based cohorts, integrating multi-source health care data could substantially improve the identification of new type 2 diabetes cases compared with relying on a single data source.