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Background: Novel diabetes phenotypes were proposed by the Europeans through cluster analysis, but Chinese community diabetes populations might exhibit different characteristics. This study aims to explore the clinical characteristics of novel diabetes subgroups under data‐driven analysis in Chinese community diabetes populations. Methods: We used K‐means cluster analysis in 6369 newly diagnosed diabetic patients from eight centers of the REACTION (Risk Evaluation of cAncers in Chinese diabeTic Individuals) study. The cluster analysis was performed based on age, body mass index, glycosylated hemoglobin, homeostatic modeled insulin resistance index, and homeostatic modeled pancreatic β‐cell functionality index. The clinical features were evaluated with the analysis of variance (ANOVA) and chi‐square test. Logistic regression analysis was done to compare chronic kidney disease and cardiovascular disease risks between subgroups. Results: Overall, 2063 (32.39%), 658 (10.33%), 1769 (27.78%), and 1879 (29.50%) populations were assigned to severe obesity‐related and insulin‐resistant diabetes (SOIRD), severe insulin‐deficient diabetes (SIDD), mild age‐associated diabetes mellitus (MARD), and mild insulin‐deficient diabetes (MIDD) subgroups, respectively. Individuals in the MIDD subgroup had a low risk burden equivalent to prediabetes, but with reduced insulin secretion. Individuals in the SOIRD subgroup were obese, had insulin resistance, and a high prevalence of fatty liver, tumors, family history of diabetes, and tumors. Individuals in the SIDD subgroup had severe insulin deficiency, the poorest glycemic control, and the highest prevalence of dyslipidemia and diabetic nephropathy. Individuals in MARD subgroup were the oldest, had moderate metabolic dysregulation and the highest risk of cardiovascular disease. Conclusion: The data‐driven approach to differentiating the status of new‐onset diabetes in the Chinese community was feasible. Patients in different clusters presented different characteristics and risks of complications. [ABSTRACT FROM AUTHOR]

Background: Not many large‐sample investigations are available that compare the potency of the relationship of remnant cholesterol (RC) and other lipid parameters with diabetes and prediabetes. The goals of our study are to discover the relationship between RC and prediabetes, diabetes, and insulin resistance (IR) and to investigate RC, high‐density lipoprotein cholesterol (HDL‐C), non‐HDL‐C, triglycerides (TG), low‐density lipoprotein cholesterol (LDL‐C), total cholesterol (TC), TC/HDL‐C, LDL‐C/HDL‐C, and TG/HDL‐C, which are the lipid parameters that are most positively related to diabetes, prediabetes, and IR. Methods: This research enrolled 36 684 subjects from China's eight provinces. We employed multiple logistic regression analysis for testing the relationship between lipid parameters and diabetes, prediabetes, and IR. Results: After adjusting for potential confounders, and comparing the results with other lipid parameters, the positive relationship between RC and diabetes (odds ratio [OR] 1.417, 95% confidence interval [CI]: 1.345–1.492), prediabetes (OR 1.555, 95% CI: 1.438–1.628), and IR (OR 1.488, 95% CI: 1.404–1.577) was highest. RC was still related to diabetes, prediabetes, and IR even when TG <2.3 mmol/L (diabetes: OR 1.256, 95% CI: 1.135–1.390; prediabetes: OR 1.503, 95% CI: 1.342–1.684; and IR: OR 1.278, 95% CI: 1.140–1.433), LDL‐C <2.6 mmol/L (diabetes: OR 1.306, 95% CI: 1.203–1.418; prediabetes: OR 1.597, 95% CI: 1.418–1.798; and IR: OR 1.552, 95% CI: 1.416–1.701), or HDL‐C ≥1 mmol/L (diabetes: OR 1.456, 95% CI: 1.366–1.550; prediabetes: OR 1.553, 95% CI: 1.421–1.697; and IR: OR 1.490, 95% CI: 1.389–1.598). Conclusion: RC is more positively related to diabetes, prediabetes, and IR than conventional lipids and lipid ratios in the general population, the relationships between RC and diabetes, prediabetes, and IR are stable, even if HDL‐C, LDL‐C, or TG are at appropriate levels. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Diabetes is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Diabetes is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Diabetes is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: This study investigated the association between birth weight and diabetes in a Chinese population, and the effects of body mass index (BMI) and lifestyle factors in later life on this association. Methods: Data from 49 118 participants aged ≥40 years with recalled birth weight from the Risk Evaluation of cAncers in Chinese diabeTic Individuals: a lONgitudinal (REACTION) study, a nationwide population‐based cohort, were used. Diabetes diagnosis was based on oral glucose tolerance tests and HbA1c measurements. Logistic regression models were used to evaluate the association of birth weight and risk of diabetes in later life. Results: Increased risk of diabetes was associated with lower or higher birth weight. Compared with individuals with a birth weight of 2500 to 3499 g, the odds ratios (ORs) and 95% confidence intervals (CIs) of diabetes for individuals with a birth weight of <2500, between 3500 and 3999, and ≥4000 g were 1.28 (1.11‐1.47), 1.11 (1.04‐1.19), and 1.20 (1.07‐1.34), respectively. Significant associations were prominent in participants with a current BMI ≥24 kg/m2, but not detected in those with a normal BMI (OR 1.20 [95% CI 0.96‐1.49], 1.11 [95% CI 0.98‐1.25], and 1.10 [95% CI 0.89‐1.37], respectively). Moreover, there was no increased risk of diabetes in individuals with a low birth weight but with healthy dietary habits (OR 0.94; 95% CI 0.68‐1.29) or ideal physical activity (OR 1.41; 95% CI 0.97‐2.04). Conclusions: A U‐shaped association was observed between birth weight and the risk of diabetes. Healthy lifestyles (healthy dietary habits or ideal physical activity) may eliminate the negative effects of low birth weight in the development of diabetes, but not the effect of high birth weight. [ABSTRACT FROM AUTHOR]

Background: Parity, pregnancy loss, and breastfeeding duration were found to be associated with diabetes. However, the results are inconsistent. Also, no epidemiological studies have examined the association of these reproductive factors with diabetes in the same large population. We aim to investigate the associations between parity, pregnancy loss, breastfeeding duration, and the risk of maternal diabetes in middle-aged and elderly Chinese females., Methods: We included 131 174 females aged ≥40 years from the REACTION study (Risk Evaluation of Cancers in Chinese Diabetic Individuals: A Longitudinal Study). Multivariable linear regression and logistic regression were used to assess the association between parity, pregnancy loss, and breastfeeding duration and type 2 diabetes., Results: The number of parities and breastfeeding duration were positively related to fasting plasma glucose, 2-hour postload glucose, glycosylated hemoglobin, and homeostatic model assessment of insulin resistance. Compared with those with one birth, nulliparous women or women with 2 or ≥3 births had a significantly increased risk of diabetes. The odds ratios (OR) and 95% confidence intervals (CI) were 1.27 (1.10-1.48), 1.17 (1.12-1.22), and 1.28 (1.21-1.35), respectively. Compared with women without pregnancy loss, those who underwent 2 (OR 1.09; 95% CI, 1.04-1.14) or ≥3 pregnancy losses (OR 1.11; 95% CI, 1.04-1.18) had an increased risk of diabetes. Moreover, women with a breastfeeding duration ≥0 to 6 months (OR 0.82; 95% CI, 0.75-0.90) and ≥6 to 12 months (OR 0.94; 95% CI, 0.89-0.99) had a significantly lower risk of diabetes., Conclusions: Nulliparous women or women with multiparity or more than one pregnancy loss have an increased risk of diabetes in later life, while women who breastfeed more than 0 to 12 months have a lower risk of diabetes., (© 2021 Ruijin Hospital, Shanghai JiaoTong University School of Medicine and John Wiley & Sons Australia, Ltd.)

Background: Age at menarche was reported to be associated with the risk of diabetes. However, the impact of ideal cardiovascular health metrics (ICVHMs) on the association between age at menarche and adulthood diabetes risk was unclear., Methods: We included 121 431 women from the nationwide, population-based cohort of the REACTION study (Risk Evaluation of Cancers in Chinese Diabetic Individuals: a Longitudinal Study). The diagnosis of diabetes was based on the oral glucose tolerance test (OGTT) and glycosylated hemoglobin (HbA1c) measurement. Logistic regression and multiplicative interaction analysis were conducted to investigate the potential interaction effect between age at menarche and ICVHMs on the development of diabetes., Results: The multivariable-adjusted odds ratios of diabetes across categories of age at menarche (<14, 14-17, and > 17 years) were 1.22 (95% confidence interval [CI]: 1.17, 1.28), 1.00 (reference), and 0.89 (95% CI: 0.85, 0.93), respectively. In subgroup analysis, significant interactions were detected between total cholesterol/blood pressure levels and age at menarche regarding the risk of diabetes (P for interaction = .0091 and .0019, respectively). The increased risk associated with age at menarche <14 years was observed in participants with three or fewer ICVHMs, but not in women with four or more ICVHMs (P for interaction = .0001)., Conclusions: Age at menarche was inversely associated with the risk of diabetes in adulthood in Chinese women, and it appeared to be modified by the presence of ICVHMs. Further studies are needed to clarify the precise interrelationship and the generalizability of our results., (© 2020 Ruijin Hospital, Shanghai JiaoTong University School of Medicine and John Wiley & Sons Australia, Ltd.)

Background: A number of primary studies suggested that active smoking could be independently associated with incident diabetes. However less is known about the effect of active smoking and smoking cessation on glycemic control in patients with diabetes. The aim of this study was to evaluate the associations of active smoking and smoking cessation with glycemic control in diabetic patients., Methods: The present was a cross-sectional study of 10 551 men and 15 297 women with diabetes from the Risk Evaluation of cAncers in Chinese diabeTic Individuals: a lONgitudinal (REACTION) study. Risk factors for glycemic control and the association of active smoking with glycemic control were evaluated using logistic regression models. Poor glycemic control was defined as HbA1c ≥7.0%., Results: Current smokers have an increased risk of poor glycemic control, and the multivariable-adjusted odds ratio (OR) and 95% confidence intervals (CI) of HbA1c ≥7.0% with current smoking were 1.49 (1.35-1.66) in men and 1.56 (1.13-2.15) in women. Further analysis demonstrated a dose-dependent relationship between active smoking and the risk of poor glycemic control in men. Former smokers who quit smoking for <10 years remained at increased risk of poor glycemic control, with the risk leveling off after 10 years of smoking cessation compared with non-smokers, but risk in former smokers was significantly lower than that in current smokers., Conclusions: Active smoking is a modifiable risk factor for poor glycemic control in Chinese diabetic patients., (© 2017 Ruijin Hospital, Shanghai Jiaotong University School of Medicine and John Wiley & Sons Australia, Ltd.)