Objective This study aimed to investigate the interaction between age groups and risk factors for diabetes and prediabetes in Shanghai communities and to identify the effect of age on other risk factors for diabetes and prediabetes. Methods This study recruited 3540 participants with undiagnosed diabetes or prediabetes in 14 communities in Shanghai from February to August 2019. All participants underwent a comprehensive examination, including filling out a detailed questionnaire, physical examination, 75 g oral glucose tolerance test, and blood sample collection. In addition, logistic regression was used to analyze the interaction between age and risk factors for prediabetes and diabetes. Results The statistical analysis included 2776 people. In this study, the prevalence of diabetes and prediabetes were 15.1% and 52.3%, respectively. The prevalence of diabetes and prediabetes is higher in the elderly than in the middle-aged group. Among the risk factors for diabetes, overweight was associated with higher age ( P -interaction 0.028). In addition, among the risk factors for prediabetes, a high level of education was associated with higher age ( P -interaction 0.039) and elevated serum cholesterol level was associated with lower age ( P -interaction 0.019). Conclusion This study confirmed an interaction between age and other influencing factors, which may be important in explaining differences in risk factors for diabetes and prediabetes in the middle-aged and elderly populations. Community health facilities can provide health guidance to people of different age groups to prevent and control prediabetes and diabetes.

BackgroundDiabetic cardiomyopathy (DCM) remains asymptomatic for many years until progression to asymptomatic left ventricular diastolic dysfunction (ALVDD), a subclinical cardiac abnormality present in early-stage DCM. Because LV function in patients with type 2 diabetes mellitus (T2DM) may be subtly altered long before the onset of ALVDD, quantitative assessment of the risk of progression to early-stage DCM in T2DM patients with normal hearts is critical for delaying or even reversing DCM.ObjectiveThis study aimed to establish a nomogram with the aid of DCM characteristics revealed by multimodal echocardiography to assess the likelihood of the progression to early-stage DCM in T2DM patients with normal cardiac function.MethodsOf the 423 T2DM patients enrolled, 302 were included in the training cohort and 121 in the validation cohort. The clinical characteristics, biochemical data, and multimodal echocardiographic parameters were collected. In the training cohort, the screened correlates of ALVDD were utilized to develop a nomogram for estimating the risk coefficient for early-stage DCM. This model was validated both in the training and validation cohorts.ResultsALVDD was independently correlated with the number of comorbidities [with one comorbidity: odds ratio (OR) = 3.009; with two comorbidities: OR = 4.026], HbA1c (OR = 1.773), myocardial blood flow (OR = 0.841), and global longitudinal strain (OR = 0.856) (all P < 0.05). They constituted a nomogram to visualize the likelihood of DCM development in T2DM patients with normal cardiac function. The model was validated to present strong discrimination and calibration, and obtained clinical net benefits both in the training and validation cohorts.ConclusionWe constructed and validated a nomogram to estimate the likelihood of developing early-stage DCM in T2DM patients with normal cardiac function. The alteration of the nomogram-predicted risk coefficient is expected to be proposed as a therapeutic target to slow or stop DCM progression.