These two datasets from Type 1 Diabetes and Type 2 Diabetes patients in Shanghai, China.

The 4th China Urban Rural Elderly Population Survey was conducted in August 2015, which was a nationwide cross-sectional survey that included 224142 elderly people aged 60 and above in China. We assessed the incidence of diabetes and related conditions through descriptive analysis and chi square analysis of demographic data, living habits, socio-economic factors and complications. Univariate and multivariate logistic regression analysis was used to describe the odds ratio (OR) of the incidence of diabetes in different groups. Stratified analysis based on gender, age, and urban-rural region. All data is collected by trained researchers according to standardized protocols. Each questionnaire has a unique number, start and end time, and the investigator's signature on the cover. Due to the large amount of information collected, we removed unnecessary information such as commuting methods and children's work for our research purposes, while retaining information such as demographic characteristics, health status, social participation, family life, psychology, etc.

ObjectiveDiabetes is a major health issue in China that has a significant economic burden on society. Understanding the economic impact of diabetes can help policymakers make informed decisions about healthcare spending and priorities. This study aims to estimate the economic burden of patients with diabetes in an urban setting in China and to identify the impact of hospitalization and complications on health care costs for people with diabetes.MethodsThe study was conducted in a sample city located in eastern China. All patients diagnosed with diabetes before January 2015 were identified from the official health management information system, and their social demographics and records of their health care uses and costs were extracted from the claim database from 2014 to 2019. Six groups of complications were identified according to ICD-10 codes. The diabetes-related direct medical cost (DM cost) was described for patients in stratified groups. A multiple linear regression model was applied to identify the effect of hospitalization and complications on the DM cost of diabetic patients.ResultsOur research included 44,994 patients with diabetes, the average annual DM costs for diabetic patients increased from 1,292.72 USD in 2014 to 2,092.87 USD in 2019. The costs of diabetes are closely related to hospitalizations and the type and number of complications. The average annual DM cost of patients who were hospitalized was 2.23 times that of those without hospitalization, and it rose as the number of complications increased. Cardiovascular complications and nephropathic complications were the complications that had the greatest impact on patients’ DM costs, increasing by an average of 65 and 54%, respectively.ConclusionThe economic burden of diabetes in urban China has increased significantly. Hospitalization and the type and number of complications have significant impacts on the economic burden of patients with diabetes. Efforts should be made to prevent the development of long-term complications in the population with diabetes.

ObjectivePrediabetes is a chronic condition characterized by elevated blood glucose levels that are not yet high enough to be classified as diabetes. It is particularly prevalent among middle-aged and elderly populations. This study aims to investigate the association between a novel marker of insulin resistance-the estimated glucose disposal rate (eGDR)-and the reversion of prediabetes to normoglycaemia or progression to diabetes in a Chinese population.MethodsThis prospective cohort study utilized baseline data from the 2011 China Health and Retirement Longitudinal Study involving 2,600 prediabetic participants aged 45 years and older, along with follow-up data from 2015. The study’s endpoints were defined according to the American Diabetes Association criteria, including maintenance of the prediabetic state, reversion to normoglycaemia, or progression to diabetes. Multivariable Cox regression models and restricted cubic spline regression were used to assess the association between eGDR and the reversion or progression of prediabetes in middle-aged and elderly populations, followed by stratified analyses to explore potential population-specific dependencies.ResultsOver a median follow-up period of 4 years, 1,615 (62.1%) participants remained in the prediabetic state, 586 (22.5%) reverted to normoglycaemia, and 399 (15.3%) progressed to diabetes. In multivariable Cox regression analyses, our results indicated that eGDR was positively associated with the reversion of prediabetes to normoglycaemia [Hazard Ratio = 1.14, 95% Confidence Interval: 1.05, 1.23], and negatively associated with the progression of prediabetes to diabetes (HR = 0.81, 95% CI: 0.70, 0.93). Restricted cubic spline analysis revealed a nonlinear, L-shaped association between eGDR and the reversion of prediabetes to normoglycaemia, with segmented Cox regression identifying an eGDR threshold of 6.81 as the point of significant change in the likelihood of prediabetes reversion.ConclusionThis prospective cohort study among middle-aged and elderly Chinese populations suggested that higher eGDR promoted the reversion of prediabetes and provided a protective effect against its progression to diabetes.

Number of incident diabetes and Hazard ratio (HR) for combined cardiovascular risk factors and psychosocial factors in older people – Hefei cohort study, China. (DOCX)

ObjectiveThis systematic review and meta-analysis aimed to evaluate the prevalence of frailty and pre-frailty in older adults with diabetes; and to identify the risk factors associated with frailty in this population.DesignSystematic review and meta-analysis.Participants24,332 people aged 60 years and older with diabetes.MethodsSix databases were searched (PubMed, Embase, the Cochrane Library, Web of Science, China Knowledge Resource Integrated Database, and Chinese Biomedical Database) up to 15 January 2024. Random effects models were used in instances of significant heterogeneity. Subgroup analysis and meta-regression were conducted to identify the potential source of heterogeneity. The Agency for Healthcare Research and Quality (AHRQ) and the Newcastle-Ottawa Scale (NOS) were applied to assess the quality of included studies.Results3,195 abstracts were screened, and 39 full-text studies were included. In 39 studies with 24,332 older people with diabetes, the pooled prevalence of frailty among older adults with diabetes was 30.0% (95% CI: 23.6%-36.7%). Among the twenty-one studies involving 7,922 older people with diabetes, the pooled prevalence of pre-frailty was 45.1% (95% CI: 38.5%-51.8%). The following risk factors were associated with frailty among older adults with diabetes: older age (OR = 1.08, 95% CI: 1.04–1.13, p

BackgroundThe association of prediabetes and diabetes on health-related quality of life (HRQoL) remains inconclusive in current epidemiological research. In this investigation, we administered 5-level EuroQoL-5 dimension version (EQ-5D-5L) to systematically assess HRQoL across glycemic strata (diabetes, prediabetes, and normal glycemic levels) in Guangzhou, and to offer baseline data that can be easily compared to other regions in China or across countries.MethodThis investigation utilized baseline cross-sectional data extracted from a three-year prospective cohort study conducted at the Health Management Center of Guangzhou 11th People’s Hospital. Propensity score matching was implemented at a 1:1:4 ratio to balance participants across diabetes, prediabetes, and normal glycemic group. HRQoL outcomes, operationalized through EQ-Index and EQ visual analog scale (EQ-VAS) measurements, were compared across groups using one-way ANOVA or Wilcoxon rank-sum tests. Multivariate linear regression was constructed to adjust for potential confounders, followed by subgroup analyses stratified by sex, age categories, body mass index (BMI) classifications, and hypertension comorbidity status.ResultsA total of 18,605 participants were included in the study. After propensity score matching, 533 participants allocated to the prediabetes group, 533 to the diabetes group, and 2064 to the normal glycemic group. Intergroup comparisons demonstrated significantly lower EQ-VAS scores in the diabetes group (79.11) compared to both prediabetes (80.67) and normal glycemic group (81.65). Similarly, the diabetes group exhibited the lowest EQ-Index scores (0.968) relative to prediabetes (0.972) and normal glycemic group (0.972). Multivariate linear regression adjusted with sex, age, BMI, etc. revealed a 2.139-point reduction in EQ-VAS scores for the diabetes group versus normal glycemic group (95% CI: -3.748, -0.530; P=0.009). Subgroup analyses identified particularly compromised HRQoL in diabetes and prediabetes populations among female participants, individuals with obesity, and those aged ≥60 years.DiscussionPrediabetes and diabetes mellitus are associated with diminished HRQoL compared to normal glycemic levels, with a more pronounced negative associations observed among female populations, older adults, and individuals with obesity. These findings emphasize the clinical necessity for implementing targeted interventions to optimize HRQoL outcomes in these high-risk subgroups, which aligns with the fundamental objectives of contemporary diabetes management frameworks.Clinical trial registrationClinicalTrials.gov ID: NCT05315895.

The burden of type 2 diabetes (T2DM) in China is significant and growing, and this is reflected in high rates of T2DM in the city of Ningbo, China. Consequent impacts on morbidity, mortality, healthcare expenditure, and health-related quality of life, make this a problem of the utmost importance to address. One way to improve T2DM outcomes is to address lifestyle behaviours that may affect prognosis and complications, such as physical activity levels, dietary habits, smoking status, and alcohol intake. A cross-sectional survey was undertaken to describe the prevalence of being physically active, having a healthy diet, currently smoking, and currently drinking alcohol among people living with T2DM attending a diabetes clinic in Ningbo, China. Regression analysis was used to determine the factors associated with these lifestyle behaviours. We found a high prevalence of a healthy diet (97.8%, 95% CI 96.5–98.7%). Prevalence of being physically active (83.4%, 95% CI 80.6–85.9%), smoking (21.6%, 95% CI 18.8–24.6%), and alcohol drinking (32.9%. 95% CI 29.6–36.2%) appeared in keeping with those of the general population. Marked associations were demonstrated between male sex and smoking (OR 41.1, 95% CI 16.2–139.0), and male sex and alcohol drinking (OR 4.00, 95% CI 2.62–6.20). Correlation between lifestyle factors was demonstrated including between alcohol drinking and smoking, and between physical activity and reduced smoking. General diabetes self-management education programmes that address multiple lifestyle risk factors simultaneously may be beneficial in this population. Specific interventions targeting smoking cessation and reduction in alcohol drinking may be of benefit to men living with T2DM attending a diabetes clinic in Ningbo.

BackgroundAlthough the association between HHEX, IGF2BP2, and FTO polymorphisms and the risk of GDM has been investigated in several studies, the findings have been inconsistent across different populations. The study aimed to investigate the association between genetic polymorphisms and GDM risk in a Chinese population.Methods502 control volunteers and 500 GDM patients were enrolled. IGF2BP2 rs11705701 and rs4402960, FTO rs9939609, and HHEX rs1111875 and rs5015480 were all genotyped using the SNPscan™ genotyping assay. The independent sample t-test, logistic regression, and chi-square test were used to assess the variations in genotype and allele and their relationships with the risk of GDM. The blood glucose level, gestational week of delivery, and newborn weight were compared using a one-way ANOVA.ResultsAfter adjusting for confounding factors, the results show that the rs1111875 heterozygous (OR=1.370; 95% CI: 1.040-1.805; P = 0.025) and overdominant (OR=1.373; 95% CI: 1.049-1.796; P = 0. 021) models are significantly associated with an increased risk of GDM, especially for the age ≥ 30 years group: heterozygote (OR=1.646; 95% CI: 1.118-2.423; P=0.012) and overdominant (OR=1.553; 95% CI: 1.064-2.266; P = 0.022) models. In the age ≥ 30 years, the rs5015480 overdominant model (OR=1.595; 95% CI: 1.034-2.459; P = 0.035) and the rs9939609 heterozygote model (OR=1.609; 95% CI: 1.016-2.550; P=0.043), allele (OR=1. 504; 95% CI: 1.006-2.248; P = 0.047), dominant model (OR=1.604; 95% CI: 1.026-2.505; P = 0.038), and overdominant model (OR=1.593; 95% CI: 1.007-2.520; P = 0.047) were associated with a significantly increased risk of GDM; Additionally, people with the TC genotype of rs1111875 had a substantially higher 1-hour blood glucose level than TT genotype (P < 0.05). The results of the meta-analysis showed that the A allele of rs11705701 was associated with an increased risk of diabetes mellitus (P < 0.05).ConclusionThe study indicates that the TC genotype of rs1111875 is linked to a higher risk of GDM, particularly in women aged 30 years or older. Additionally, rs5015480 and rs9939609 were significantly associated with GDM in the same age group. These SNPs may therefore be more closely linked to GDM in older mothers.

ObjectiveSeveral studies have shown that miR-146a rs2910164 (C > G) is associated with type 2 diabetes mellitus (T2DM) susceptibility, but the results are still controversial. This study is divided into two parts, and one is to explore the relationship between miR-146a rs2910164 polymorphism and the genetic susceptibility of T2DM in Chinese Han population. Second, a meta-analysis on the basis of a larger sample size was used to determine whether this is a susceptibility gene for T2DM.MethodsA case–control study including 574 T2DM patients and 596 controls was used to evaluate the association of miR-146a rs2910164 polymorphism with the risk of T2DM in Chinese Han People. Then, we systematically searched studies investigating the correlation between miR-146a rs2910164 polymorphism and T2DM susceptibility published before April 2022 from PubMed, Web of Science, Wanfang, and China National Knowledge Infrastructure database, and a meta-analysis including six studies was carried out. The results were expressed by odds ratio (OR) and its 95% confidence interval (95% CI).ResultsIn a case–control study, we found that there were no statistical differences in genotype frequencies between T2DM and control group. Subgroup analysis showed that, compared with the CC genotype, CG + GG genotype was associated with a decreased risk of T2DM in the subgroup of individuals ≥ 65 years old (OR = 0.75; 95% CI: 0.58–0.98; Padjusted = 0.032) and BMI < 18.5 (OR = 0.16; 95% CI: 0.03–0.89; Padjusted = 0.037). In overall meta-analysis, significant heterogeneity was detected. No significant association between miR-146a rs2910164 polymorphism and T2DM was observed in all genetic models under random effects models. Subgroup analysis revealed that there was a significant difference in genotype frequencies between the T2DM and control group in recessive model (CC vs. CG + GG: OR = 1.79; 95% CI: 1.08–2.96; PQ = 0.307, I2 = 4.0%) and homozygote model (CC vs. GG: OR = 1.79; 95% CI: 1.07–3.00; PQ = 0.216, I2 = 34.7%) in Caucasians.ConclusionThe results of our study demonstrate that the miR-146a rs2910164 polymorphism might have ethnicity-dependent effects in T2DM and may be related to T2DM susceptibility in Caucasians.

BackgroundAccumulating evidence has revealed that the aspartate aminotransferase to alanine aminotransferase (AST/ALT) ratio is a promising novel biomarker for insulin resistance (IR) and metabolic diseases. However, research on the association between the AST/ALT ratio and the incidence of diabetes progressing from prediabetes remains lacking. Herein, this study aimed to evaluate the relationship between the baseline AST/ALT ratio and risks of diabetes in patients with prediabetes.MethodsThis was a retrospective cohort study involving a total of 82,683 participants across 32 regions and 11 cities in China from 2010 to 2016. Data was obtained based on the DATADRYAD database from the health check screening program. Participants were stratified according to the interquartile range of the AST/ALT ratio (groups Q1 to Q4). The Cox proportional hazard model and smooth curve fitting were used to explore the relationship between the baseline AST/ALT ratio and the risk of diabetes in prediabetic patients. In addition, subgroup analysis was used to further validate the stability of the results.ResultsThe mean age of the selected participants was 49.9 ± 14.0 years, with 66.8% of them being male. During the follow-up period 1,273 participants (11.3%) developed diabetes progressing from prediabetes during the follow-up period. Participants who developed diabetes were older and were more likely to be male. The fully-adjusted Cox proportional hazard model revealed that the AST/ALT ratio was negatively associated with the risk of diabetes in prediabetic patients (HR = 0.40, 95% CI: 0.33 to 0.48, P < 0.001). Higher AST/ALT ratio groups (Q4) also presented with a lower risk of progressing into diabetes (HR = 0.35, 95% CI: 0.29 to 0.43, P < 0.001, respectively) compared with the lowest quintile group (Q1). Through subgroup analysis and interaction tests, it was found that the association stably existed in all subgroup variables, and there were a stronger interactive effects in people with age < 45 years, and TG ≤ 1.7 mmol/L in the association between AST/ALT ratio and diabetes incidences in patients with prediabetes (P for interaction < 0.05).ConclusionAccording to our study, a higher AST/ALT ratio is associated with a lower risk of progressing into diabetes from prediabetes. Regular monitoring of AST/ALT ratio dynamics and corresponding interventions can help prevent or slow prediabetes progression for diabetes.

BackgroundAccumulating evidence has revealed that the aspartate aminotransferase to alanine aminotransferase (AST/ALT) ratio is a promising novel biomarker for insulin resistance (IR) and metabolic diseases. However, research on the association between the AST/ALT ratio and the incidence of diabetes progressing from prediabetes remains lacking. Herein, this study aimed to evaluate the relationship between the baseline AST/ALT ratio and risks of diabetes in patients with prediabetes.MethodsThis was a retrospective cohort study involving a total of 82,683 participants across 32 regions and 11 cities in China from 2010 to 2016. Data was obtained based on the DATADRYAD database from the health check screening program. Participants were stratified according to the interquartile range of the AST/ALT ratio (groups Q1 to Q4). The Cox proportional hazard model and smooth curve fitting were used to explore the relationship between the baseline AST/ALT ratio and the risk of diabetes in prediabetic patients. In addition, subgroup analysis was used to further validate the stability of the results.ResultsThe mean age of the selected participants was 49.9 ± 14.0 years, with 66.8% of them being male. During the follow-up period 1,273 participants (11.3%) developed diabetes progressing from prediabetes during the follow-up period. Participants who developed diabetes were older and were more likely to be male. The fully-adjusted Cox proportional hazard model revealed that the AST/ALT ratio was negatively associated with the risk of diabetes in prediabetic patients (HR = 0.40, 95% CI: 0.33 to 0.48, P < 0.001). Higher AST/ALT ratio groups (Q4) also presented with a lower risk of progressing into diabetes (HR = 0.35, 95% CI: 0.29 to 0.43, P < 0.001, respectively) compared with the lowest quintile group (Q1). Through subgroup analysis and interaction tests, it was found that the association stably existed in all subgroup variables, and there were a stronger interactive effects in people with age < 45 years, and TG ≤ 1.7 mmol/L in the association between AST/ALT ratio and diabetes incidences in patients with prediabetes (P for interaction < 0.05).ConclusionAccording to our study, a higher AST/ALT ratio is associated with a lower risk of progressing into diabetes from prediabetes. Regular monitoring of AST/ALT ratio dynamics and corresponding interventions can help prevent or slow prediabetes progression for diabetes.

BackgroundPeople with diabetes mellitus (DM) have a significantly increased risk of sarcopenia. A cross-sectional analysis was performed using nationally representative data to evaluate possible sarcopenia in middle-aged and older adults with diabetes mellitus, and to develop and validate a prediction model suitable for possible sarcopenia in middle-aged and older adults with diabetes mellitus in the Chinese community.MethodsData from the China Health and Retirement Longitudinal Study (CHARLS), which focuses on people 45 years of age or older, served as the basis for the prediction model. CHARLS 2015 participants were used in the study, which examined 53 factors. In order to guarantee model reliability, the study participants were split into two groups at random: 70% for training and 30% for validation. Ten-fold cross-validation and Least Absolute Shrinkage and Selection Operator (LASSO) regression analyses were used to determine the best predictors for the model. The factors associated with sarcopenia in DM were researched using logistic regression models. Nomogram were constructed to develop the predictive model. The performance of the model was assessed using area under the curve (AUC), calibration curves and decision curve analysis (DCA).ResultsA total of 2,131 participants from the CHARLS database collected in 2015 passed the final analysis, and the prevalence of sarcopenia was 28.9% (616/2131). Eight factors were subsequently chosen as predictive models by LASSO logistic regression: age, residence, body mass index, diastolic blood pressure, cognitive function, activities of daily living, peak expiratory flow and hemoglobin. These factors were used in the nomogram predictive model, which showed good accuracy and agreement. The AUC values for the training and validation sets were 0.867 (95%CI: 0.847~0.887) and 0.849 (95%CI: 0.816~0.883). Calibration curves and DCA indicated that the nomogram model exhibited good predictive performance.ConclusionThe nomogram predictive model constructed in this study can be used to evaluate the probability of sarcopenia in middle-aged and older adult DM, which is helpful for early identification and intervention of high-risk groups.

Possible channels of influence of income inequality.