A Prediction Model for Prediabetes Risk in Middle-Aged and Elderly Populations: A Prospective Cohort Study in China.
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ABSTRACT: Background
To investigate indicators for prediabetes risk and construct a prediction model for prediabetes incidences in China.Methods
In this study, 551 adults aged 40-70 years had normal glucose tolerance (NGT) and normal hemoglobin A1c (HbA1c) levels at baseline. Baseline data including demographic information, anthropometric measurements, and metabolic profile measurements were collected. The associations between possible indicators and prediabetes were assessed by the Cox proportional-hazards model. The predictive values were evaluated by the area under the receiver operating characteristic (ROC) curve (AUC).Results
During an average of 3.35 years of follow-up, the incidence of prediabetes was found to be 19.96% (n = 110). In the univariate analyses, fasting plasma glucose (FPG), fasting serum insulin (FINS), 2 h plasma glucose (2hPG), HbA1c, serum uric acid (SUA), waist circumference (WC), smoking, and family history of diabetes (FHD) were found to be significantly correlated with prediabetes. In the multivariable analyses, WC (hazard ratio (HR): 1.032; 95% confidence interval (CI): 1.010, 1.053; p = 0.003), FHD (HR: 1.824; 95% CI: 1.250, 2.661; p = 0.002), HbA1c (HR: 1.825; 95% CI: 1.227, 2.714; p = 0.003), and FPG (HR: 2.284; 95% CI: 1.556, 3.352; p < 0.001) were found to be independent risk factors for prediabetes. A model that encompassed WC, FHD, HbA1c, and FPG for predicting prediabetes exhibited the largest discriminative ability (AUC: 0.702).Conclusions
WC, FHD, HbA1c, and FPG are independently correlated with the risk of prediabetes. Furthermore, the combination of these predictors enhances the predictive accuracy of prediabetes.
SUBMITTER: Wu J
PROVIDER: S-EPMC8601847 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundLimited studies have explored the predictive efficiency of prediabetes based on two definitions for diabetes among Chinese middle-aged and older populations with prediabetes.ObjectiveTo evaluate the predictive efficiency of prediabetes based on two definitions for diabetes and the clinical and public health benefit in Chinese middle-aged and older populations.DesignA 5-year cohort study from the China Health and Retirement Longitudinal Study.ParticipantsA total of 5208 participants who had blood sample data at baseline in 2011.Main measuresThe exposure was prediabetes based on American Diabetes Association (ADA) and World Health Organization (WHO) definition. The main outcome was incident diabetes. The ability of prediabetes for predicting diabetes was assessed by sensitivity, specificity, positive predictive value, and negative predictive value. Cox proportional hazards regression was used to explore the associations between prediabetes and the 5-year risk of diabetes and all-cause mortality.Key resultsAmong those with prediabetes according to the ADA definition, only 426 (15.45%) with baseline prediabetes progressed to total diabetes, while according to the WHO definition, 208 (21.89%) progressed to total diabetes. In terms of the ability of predicting the incident total diabetes in 5 years, the ADA definition has a higher sensitivity than the WHO definition (70.76% versus 34.55%, P < 0.001), while the WHO definition has a higher specificity than the ADA definition (84.09% versus 49.35%, P < 0.001). Positive predictive values based on the two definitions were low (< 24%); negative predictive values were high (> 90%).ConclusionsNeither definition of prediabetes is robust for predicting diabetes development in Chineses middle-aged and older populations.
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Project description:PurposeOur aim was to investigate prospective associations of consumption of total dairy and dairy types with incident prediabetes in a Dutch population-based study.MethodsTwo enrolment waves of the Hoorn Studies were harmonized, resulting in an analytic sample of 2262 participants without (pre-) diabetes at enrolment (mean age 56 ± 7.3 years; 50% male). Baseline dietary intake was assessed by validated food frequency questionnaires. Relative risks (RRs) were calculated between dairy, fermented dairy, milk, yogurt (all total/high/low fat), cream and ice cream and prediabetes. Additionally, substituting one serving/day of dairy types associated with prediabetes with alternative dairy types was analysed.ResultsDuring a mean 6.4 ± 0.7 years of follow-up, 810 participants (35.9%) developed prediabetes. High fat fermented dairy, cheese and high fat cheese were associated with a 17% (RR 0.83, 95% CI 0.69-0.99, ptrend = 0.04), 14% (RR 0.86, 95% CI 0.73-1.02, ptrend = 0.04) and 21% (RR 0.79, 95% CI 0.66-0.94, ptrend = 0.01) lower risk of incident prediabetes, respectively, in top compared to bottom quartiles, after adjustment for confounders. High fat cheese consumption was continuously associated with lower prediabetes risk (RRservings/day 0.94, 95% CI 0.88-1.00, p = 0.04). Total dairy and other dairy types were not associated with prediabetes risk in adjusted models, irrespective of fat content (RR ~ 1). Replacing high fat cheese with alternative dairy types was not associated with prediabetes risk.ConclusionThe highest intake of high fat fermented dairy, cheese and high fat cheese were associated with a lower risk of prediabetes, whereas other dairy types were not associated. Cheese seems to be inversely associated with type 2 diabetes risk, despite high levels of saturated fatty acids and sodium.
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Project description:BackgroundPrediabetes progression is associated with increased mortality while its regression decreases it. It is unclear whether muscle strength is related to prediabetes progression or regression. This study investigated the associations of muscle strength, assessed by grip strength and chair-rising time, with prediabetes progression and regression based on the China Health and Retirement Longitudinal Study (CHARLS) enrolling middle-aged and older adults.MethodsWe included 2623 participants with prediabetes from CHARLS, who were followed up 4 years later with blood samples collected for measuring fasting plasma glucose and haemoglobin A1c. Grip strength (normalized by body weight) and chair-rising time were assessed at baseline and categorized into tertiles (low, middle, and high groups). Prediabetes at baseline and follow-up was defined primarily using the American Diabetes Association (ADA) criteria and secondarily using the World Health Organization (WHO) and International Expert Committee (IEC) criteria. Multinomial logistic regression analysis was applied to obtain the odds ratios (ORs) and 95% confidence intervals (CIs).ResultsThe mean age of included participants was 59.0 ± 8.6 years, and 46.6% of them were males. During follow-up, 1646 participants remained as prediabetes, 379 progressed to diabetes, and 598 regressed to normoglycaemia based on ADA criteria. Participants who progressed to diabetes had lower normalized grip strength than those who remained as prediabetes (0.49 ± 0.15 vs. 0.53 ± 0.15, P < 0.001), but participants who regressed to normoglycaemia showed the opposite (0.55 ± 0.16 vs. 0.53 ± 0.15, P = 0.003). However, chair-rising time was comparable across different groups (Poverall = 0.17). Compared with participants in low normalized grip strength or high chair-rising time group, those in high normalized grip strength or low chair-rising time group had decreased odds of progression to diabetes (OR 0.62, 95% CI 0.44 to 0.87; and OR 0.69, 95% CI 0.51 to 0.93, respectively) after multivariable adjustment. However, both were unrelated to the odds of regression to normoglycaemia (OR 0.94, 95% CI 0.71 to 1.25; and OR 0.84, 95% CI 0.65 to 1.07, respectively). These outcomes remained generally comparable when prediabetes was defined by WHO or IEC criteria. Higher normalized grip strength but not lower chair-rising time was prospectively associated with lower blood pressure, better glycaemic condition, and lower inflammation (all P ≤ 0.04).ConclusionsHigh muscle strength is associated with reduced odds of progression to diabetes but does not predict regression to normoglycaemia in prediabetes. Future studies are warranted to assess whether increases in muscle strength promote prediabetes regression.
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Project description:IntroductionKidney stone risk factors are understudied among Asians. Our study objective was to investigate associations of obesity and other chronic diseases with incident kidney stones among the urban Chinese.Patients and methodsIncluded in this study are two prospective cohorts: the Shanghai Women's Health Study (N?=?69,166) and Shanghai Men's Health Study (N?=?58,054). Incident kidney stones were determined by self-report in 2004 and 2008. Cox regression models were used to evaluate the associations of study variables with stone risk with adjustment of demographics, medical history, and dietary intakes.ResultsThere were 2653 incident stones over 1,007,958 person-years of follow-up. Overall incidence rates (per 1000 person-years, 95% confidence interval [CI]) were 2.10 (1.99, 2.21) among women and 3.80 (3.59, 4.02) among men. Higher body mass index (BMI) was associated with risk (BMI ?25 vs 18.5-24.9?kg/m2, women: hazard ratio [HR]?=?1.14 [95% CI 1.01, 1.28]; men: HR?=?1.17 [1.03, 1.32]). High waist-hip ratio (?0.80 and ?0.90 for women and men, respectively) was associated with risk (HR 1.13, 95% CI 1.01, 1.27 for women; HR 1.19, 95% CI 1.05, 1.35 for men). Coronary heart disease or stroke history was associated with risk in women only (HR 1.31, 95% CI 1.10, 1.56). Hypertension history was associated with risk in men only (HR 1.27, 95% CI 1.11, 1.45). No significant association with diabetes mellitus was observed.ConclusionsAmong the Chinese, kidney stone incidence in men is almost twice that of women. Obesity is a shared risk factor. Hypertension history is associated with risk in men, whereas history of coronary heart disease or stroke is associated with risk in women.
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Project description:BackgroundDiabetes mellitus, especially type 2 diabetes mellitus (T2DM), is regarded as highly heterogeneous. Novel diabetes phenotypes by cluster analysis have been proposed in Europeans but may show different cluster features in Asians. The applicability of cluster analysis in middle-aged and elderly Chinese community T2DM patients needs further investigation.MethodsParticipants were recruited from Jiading community in Shanghai, China. We adopted k-means cluster analysis in 1130 patients (aged ≥ 40 years) with newly-diagnosed T2DM at baseline. Cluster analysis was performed based on seven variables, including fasting plasma glucose, 2 hours postprandial blood glucose, age at diagnosis, body mass index, hemoglobin A1c, homoeostatic model assessment estimates of β-cell function and insulin resistance. All subjects were re-examined at 4.4 years later. Metabolic associated fatty liver disease was diagnosed using B-ultrasound, hepatic fibrosis by non-invasive scores, renal and cardiovascular status by subclinical biomarkers. Multivariable logistic regression models were used to compare the risks of complications between clusters.ResultsPatients were classified into 4 clusters. 381 (33.7%), 456 (40.4%), 87 (7.7%), and 206 (18.2%) patients were separately assigned to mild age-related diabetes (MARD), mild obesity-related diabetes (MOD), severe insulin-deficient and insulin-resistant diabetes (SIDRD), or severe obesity-related and insulin-resistant diabetes (SOIRD), respectively. Participants in MARD, SOIRD, and SIDRD clusters were associated with significantly increased risks of different complications. SOIRD and SIDRD showed novel features in Chinese T2DM patients that were different from those in Europeans.ConclusionsThe refined diabetes phenotypic approach was applicable to Chinese middle-aged and elderly T2DM patients. Patients in different clusters presented significantly different characteristics, progression of metabolic features, and risks of diabetic complications.
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Project description:ObjectivesThis study aimed to examine the prevalence and risk factors of dyslipidemia in different diabetic progression stages among middle-aged and elderly Chinese populations.MethodsThe 2010-2012 China National Nutrition and Health Survey (CNNHS) is a nationally representative cross-sectional study. In the present study, a total of 69,974 participants aged ≥ 45 years were included. Dyslipidemia was defined based on the Chinese adult dyslipidemia prevention guide. A multivariable logistic regression model was performed to examine the associations between risk factors and dyslipidemia.ResultsThe prevalence of dyslipidemia was 39.9%, 46.8%, and 59.3% in participants with normal glucose, prediabetes, and type 2 diabetes mellitus (T2DM). Women had a lower dyslipidemia prevalence than men (38.7% vs. 43.3%). Dyslipidemia prevalence was positively associated with the education level and inversely correlated with the physical activity level, and negatively related to age only among prediabetes and T2DM groups (P for trend < 0.05). Obesity, abdominal obesity, and hypertension were associated with dyslipidemia.ConclusionsThe prevalence of dyslipidemia was relatively high among middle-aged and elderly T2DM person. There are different associations between multiple risk factors and dyslipidemia in different diabetic progression stages.
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Project description:ObjectiveTo develop and internally validate a prediction model for 6-year risk of stroke and its primary subtypes in middle-aged and elderly Chinese population.DesignThis is a retrospective cohort study from a prospectively collected database.ParticipantsWe included a total 3124 adults aged 45-80 years, free of stroke or myocardial infarction at baseline in the 2009-2015 cohort of China Health and Nutrition Survey.Primary and secondary outcome measuresThe outcome of the prediction model was stroke. Investigated predictors were: age, gender, body mass index (BMI), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), total cholesterol (TC), hypertension (HBP), drinking status, smoking status, diabetes and site. Stepwise multiple Cox regression was applied to identify independent predictors. A nomogram was constructed to predict 6-year risk of stroke based on the multiple analysis results. Bootstraps with 1000 resamples were applied to both C-index and calibration curve.ResultThe overall incidence of overall stroke was 2.98%. Age, gender, HBP and TC were found as significant risk predictors for overall stroke; age, gender, HBP and LDL-C were found as significant risk predictors for ischaemic stroke; age, gender, HBP, BMI and HDL-C were found as significant risk predictors for haemorrhagic stroke. The nomogram was constructed using significant variables included in the model, with a C-index of 0.74 (95% CI: 0.72 to 0.76), 0.74 (95% CI: 0.71 to 0.77), and 0.81 (95% CI: 0.78 to 0.84) for overall stroke, ischaemic stroke, and haemorrhagic stroke model, respectively. The calibration curves demonstrated the good agreements between predicted and observed 6-year risk probability.ConclusionOur nomogram could be convenient, easy to use and effective prognoses for predicting 6-year risk of stroke in middle-aged and elderly Chinese population.
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Project description:The predictive value of traditional cardiovascular risk estimators is limited, and young and elderly populations are particularly underrepresented. We aimed to investigate the urine metabolome and its association with cardiovascular risk to identify novel markers that might complement current estimators based on age. Urine samples were collected from 234 subjects categorized into three age-grouped cohorts: 30-50 years (cohort I, young), 50-70 years (cohort II, middle-aged), and > 70 years (cohort III, elderly). Each cohort was further classified into three groups: (a) control, (b) individuals with cardiovascular risk factors, and (c) those who had a previous cardiovascular event. Novel urinary metabolites linked to cardiovascular risk were identified by nuclear magnetic resonance in cohort I and then evaluated by target mass spectrometry quantification in all cohorts. A previously identified metabolic fingerprint associated with atherosclerosis was also analyzed and its potential risk estimation investigated in the three aged cohorts. Three different metabolic signatures were identified according to age: 2-hydroxybutyrate, gamma-aminobutyric acid, hypoxanthine, guanidoacetate, oxaloacetate, and serine in young adults; citrate, cyclohexanol, glutamine, lysine, pantothenate, pipecolate, threonine, and tyramine shared by middle-aged and elderly adults; and trimethylamine N-oxide and glucuronate associated with cardiovascular risk in all three cohorts. The urinary metabolome contains a metabolic signature of cardiovascular risk that differs across age groups. These signatures might serve to complement existing algorithms and improve the accuracy of cardiovascular risk prediction for personalized prevention. KEY MESSAGES: • Cardiovascular risk in the young and elderly is underestimated. • The urinary metabolome reflects cardiovascular risk across all age groups. • Six metabolites constitute a metabolic signature of cardiovascular risk in young adults. • Middle-aged and elderly adults share a cardiovascular risk metabolic signature. • TMAO and glucuronate levels reflect cardiovascular risk across all age groups.
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Project description:ObjectivesSelf-treatment is a widespread practice among patients with common symptoms and ailments; it is necessary to explore multiple aspects of it. Notably, there is little research into self-treatment among middle-aged and elderly people, who are more likely to fall ill. Our goals are to provide a comprehensive description of self-treatment and explore associated factors with insurance utilization and expenditures among the middle-aged and elderly populations in China.MethodsA survey was conducted in July 2016 in Shanxi, China. A stratified sampling scheme was applied to achieve representativeness. A total of 972 subjects were surveyed. Descriptive statistics, t- and Chi-squared tests, multivariate logistic regression, and multivariate linear regression were utilized.ResultsIn our study, 772 (79.4%) of the surveyed subjects self-treated during the previous twelve months. Among them, 253 (32.8%) used health insurance. Subjects' characteristics were associated with insurance utilization and expenditures for self-treatment. Total cost was positively associated with insurance utilization. The subjects with a junior high education (p-value < 0.001, aOR = 0.049) and senior high education (p-value = 0.020, aOR = 0.146) had a lower probability of using insurance. For both total costs and out-of-pocket costs, subjects who were 51 to 60 years old had lower costs. The subjects who were seriously sick and had a primary school education, as well as enterprise occupations, had higher costs. Self-treatment times were also positively associated with costs. Finally, it was found that subjects who didn't use insurance had lower total costs.ConclusionsThe prevalence of self-treatment was high (79.4%). Some characteristics were associated with insurance utilization and expenditures in self-treatment. Our results may be helpful for policy interventions, which are needed to further improve the effectiveness of health insurance in China.
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Project description:BACKGROUND: In the evaluation of a healthcare system, it is of interest to identify factors associated with the usage of different healthcare facilities and with different levels of medical expenditure. METHODS: A survey was conducted in January and February of 2012 in China. It focused on the middle-aged and elderly with age of 45 and above. A total of 2,093 people from 1,152 households were surveyed. RESULTS: For inpatient treatment, the probability of using grade III hospitals, which had the highest level of care, was positively associated with age, being married, living in urban areas, and having higher income. For outpatient treatment, the probability of using grade III hospitals was positively associated with age, being married, working in enterprises, living in urban areas, living in central and western regions, and having higher income, and negatively associated with being farmers. The total and out-of-pocket (OOP) medical expenses were analyzed separately. It was found that the expense level was associated with age, education, occupation, living in urban areas, type of hospital used, insurance being used, and per capita income. CONCLUSION: The access to healthcare and level of medical expenditure were found as associated with demographic characteristics. In addition, differences between areas and regions were observed. Such results may be useful for identifying vulnerable population and for tuning future healthcare development policies.
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