ResearchPad - epidemiology-health-services-research https://www.researchpad.co Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[Glycated hemoglobin (HbA1c) as diagnostic criteria for diabetes: the optimal cut-off points values for the Pakistani population; a study from second National Diabetes Survey of Pakistan (NDSP) 2016–2017]]> https://www.researchpad.co/article/elastic_article_12517 Glycated hemoglobin (HbA1c) cut-off values as diagnostic tool in diabetes and prediabetes with its concordance to oral glucose tolerance test (OGTT) in Pakistani population.MethodologyData for this substudy was obtained from second National Diabetes Survey of Pakistan (NDSP) 2016–2017. With this survey, 10 834 individuals were recruited and after excluding known subjects with diabetes, 6836 participants fulfilled inclusion criteria for this study. Demographic, anthropometric and biochemical parameters were obtained. OGTT was used as standard diagnostic tool to screen population and HbA1c for optimal cut-off values. Participants were categorized into normal glucose tolerance (NGT), newly diagnosed diabetes (NDD) and prediabetes.ResultsOut of 6836 participants, 4690 (68.6%) had NGT, 1333 (19.5%) had prediabetes and 813 (11.9%) had NDD by OGTT criteria with median (IQR) age of 40 (31–50) years. Optimal HbA1c cut-off point for identification of diabetes and prediabetes was observed as 5.7% ((AUC (95% CI)=0.776 (0.757 to 0.795), p<0.0001)) and 5.1% ((AUC (95% CI)=0.607 (0.590 to 0.624), p<0.0001)), respectively. However, out of 68.6% NGT subjects identified through OGTT, 24.1% and 9.3% participants were found to have prediabetes and NDD, respectively by using HbA1c criteria. By using both OGTT and HbA1c criteria, only 7.9% and 7.3% were observed as prediabetes and diabetes, respectively.ConclusionFindings from second NDSP demonstrated disagreement between findings of OGTT and HbA1c as diagnostic tool for Pakistani population. As compared with international guidelines, HbA1c threshold for prediabetes and NDD were lower in this part of world. HbA1c as diagnostic tool might require ethnic or regional-based modification in cut-off points, validated by relevant community-based epidemiological surveys. ]]> <![CDATA[FINDRISC in Latin America: a systematic review of diagnosis and prognosis models]]> https://www.researchpad.co/article/elastic_article_9104 This review aimed to assess whether the FINDRISC, a risk score for type 2 diabetes mellitus (T2DM), has been externally validated in Latin America and the Caribbean (LAC). We conducted a systematic review following the CHARMS (CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies) framework. Reports were included if they validated or re-estimated the FINDRISC in population-based samples, health facilities or administrative data. Reports were excluded if they only studied patients or at-risk individuals. The search was conducted in Medline, Embase, Global Health, Scopus and LILACS. Risk of bias was assessed with the PROBAST (Prediction model Risk of Bias ASsessment Tool) tool. From 1582 titles and abstracts, 4 (n=7502) reports were included for qualitative summary. All reports were from South America; there were slightly more women, and the mean age ranged from 29.5 to 49.7 years. Undiagnosed T2DM prevalence ranged from 2.6% to 5.1%. None of the studies conducted an independent external validation of the FINDRISC; conversely, they used the same (or very similar) predictors to fit a new model. None of the studies reported calibration metrics. The area under the receiver operating curve was consistently above 65.0%. All studies had high risk of bias. There has not been any external validation of the FINDRISC model in LAC. Selected reports re-estimated the FINDRISC, although they have several methodological limitations. There is a need for big data to develop—or improve—T2DM diagnostic and prognostic models in LAC. This could benefit T2DM screening and early diagnosis.

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<![CDATA[Variability in estimated glomerular filtration rate and the incidence of type 2 diabetes: a nationwide population-based study]]> https://www.researchpad.co/article/elastic_article_9085 Variability in estimated glomerular filtration rate (eGFR) has been associated with adverse outcomes in patients with diabetes or chronic kidney disease (CKD). However, no previous study has explored the relationship between eGFR variability and type 2 diabetes incidence.Research design and methodsIn this nationwide, longitudinal, cohort study, we investigated the association between eGFR variability and type 2 diabetes risk using the Korean National Health Insurance Service datasets from 2002 to 2017. eGFR variability was calculated using the variability independent of the mean (eGFR-VIM), coefficient of variation (eGFR-CV), standard deviation (eGFR-SD) and average real variability (eGFR-ARV).ResultsWithin 7 673 905.58 person-years of follow-up (mean follow-up: 3.19 years; n=2 402 668), 11 981 cases of incident type 2 diabetes were reported. The HRs and 95% CIs for incident type 2 diabetes increased according to advance in quartiles of eGFR-VIM (HR (95% CI): Q2, 1.068 (1.009 to 1.130); Q3, 1.077 (1.018 to 1.138); Q4, 1.203 (1.139 to 1.270)) even after adjusting for confounding factors including mean eGFR and mean fasting plasma glucose levels. The subgroup analyses according to risk factors as well as analyses using eGFR-CV, eGFR-SD and eGFR-ARV showed consistent results. The association between increased eGFR variability and type 2 diabetes risk was more prominent in men, individuals with dyslipidemia and those with CKD as shown in the subgroup analysis (p for interaction <0.001).ConclusionsIncreased eGFR variability may be an independent predictor of type 2 diabetes and might be useful for risk stratification of individuals without diabetes. ]]> <![CDATA[Association of fasting plasma glucose variability with gestational diabetes mellitus: a nationwide population-based cohort study]]> https://www.researchpad.co/article/elastic_article_9084 Long-term glycemic variability has recently been recognized as another risk factor for future adverse health outcomes. We aimed to evaluate the risk of gestational diabetes mellitus (GDM) according to the prepregnancy long-term fasting plasma glucose (FPG) variability.Research design and methodsA total of 164 053 women who delivered their first baby between January 1, 2012 and December 31, 2015, were selected from the Korean National Health Insurance data. All women underwent at least three national health screening examinations, and the last examination should be conducted within 2 years before their first delivery. GDM was defined as the presence of more than four times of claim of GDM (International Classification of Disease, 10th Revision (ICD-10) O24.4 and O24.9) or prescription of insulin under the ICD-code of GDM. FPG variability was assessed by variability independent of the mean (FPG-VIM), coefficient of variation, SD, and average successive variability.ResultsAmong the 164 053 women, GDM developed in 6627 (4.04%). Those in the higher quartiles of FPG-VIM showed a stepwise increased risk of GDM. In fully adjusted model, the ORs for GDM was 1.22 (95% CI 1.14 to 1.31) in women with the highest FPG-VIM quartile compared with those in the lowest quartile. The risk for GDM requiring insulin therapy was 48% increase in women in the highest quartile of FPG-VIM compared with those in the lowest quartile, while that for GDM not requiring insulin therapy was 19% increase. The association between high FPG variability and the risk of GDM was intensified in the obese and aged more than 35 years women.ConclusionsIncreased FPG variability in the prepregnancy state is associated with the risk of GDM independent of confounding factors. Therefore, prepregnancy FPG variability might be a surrogate marker of the risk of GDM. ]]> <![CDATA[Shared genetic architecture and casual relationship between leptin levels and type 2 diabetes: large-scale cross-trait meta-analysis and Mendelian randomization analysis]]> https://www.researchpad.co/article/elastic_article_9083 We aimed to estimate genetic correlation, identify shared loci and test causality between leptin levels and type 2 diabetes (T2D).Research design and methodsOur study consists of three parts. First, we calculated the genetic correlation of leptin levels and T2D or glycemic traits by using linkage disequilibrium score regression analysis. Second, we conducted a large-scale genome-wide cross-trait meta-analysis using cross-phenotype association to identify shared loci between trait pairs that showed significant genetic correlations in the first part. In the end, we carried out a bidirectional MR analysis to find out whether there is a causal relationship between leptin levels and T2D or glycemic traits.ResultsWe found positive genetic correlations between leptin levels and T2D (Rg=0.3165, p=0.0227), fasting insulin (FI) (Rg=0.517, p=0.0076), homeostasis model assessment-insulin resistance (HOMA-IR) (Rg=0.4785, p=0.0196), as well as surrogate estimates of β-cell function (HOMA-β) (Rg=0.4456, p=0.0214). We identified 12 shared loci between leptin levels and T2D, 1 locus between leptin levels and FI, 1 locus between leptin levels and HOMA-IR, and 1 locus between leptin levels and HOMA-β. We newly identified eight loci that did not achieve genome-wide significance in trait-specific genome-wide association studies. These shared genes were enriched in pancreas, thyroid gland, skeletal muscle, placenta, liver and cerebral cortex. In addition, we found that 1-SD increase in HOMA-IR was causally associated with a 0.329 ng/mL increase in leptin levels (β=0.329, p=0.001).ConclusionsOur results have shown the shared genetic architecture between leptin levels and T2D and found causality of HOMA-IR on leptin levels, shedding light on the molecular mechanisms underlying the association between leptin levels and T2D. ]]> <![CDATA[Association between pre-diabetes and microvascular and macrovascular disease in newly diagnosed type 2 diabetes]]> https://www.researchpad.co/article/elastic_article_9081 The associated risk of vascular disease following diagnosis of type 2 diabetes in people previously identified as having pre-diabetes in real-world settings is unknown. We examined the presence of microvascular and macrovascular disease in individuals with newly diagnosed type 2 diabetes by glycemic status within 3 years before diagnosis.Research design and methodsWe identified 159 736 individuals with newly diagnosed type 2 diabetes from the UK Clinical Practice Research Datalink database in England between 2004 and 2017. We used logistic regression models to compare presence of microvascular (retinopathy and nephropathy) and macrovascular (acute coronary syndrome, cerebrovascular and peripheral arterial disease) disease at the time of type 2 diabetes diagnosis by prior glycemic status.ResultsHalf of the study population (49.9%) had at least one vascular disease, over one-third (37.4%) had microvascular disease, and almost a quarter (23.5%) had a diagnosed macrovascular disease at the time of type 2 diabetes diagnosis.Compared with individuals with glycemic values within the normal range, those detected with pre-diabetes before the diagnosis had 76% and 14% increased odds of retinopathy and nephropathy (retinopathy: adjusted OR (AOR) 1.76, 95% CI 1.69 to 1.85; nephropathy: AOR 1.14, 95% CI 1.10 to 1.19), and 7% higher odds of the diagnosis of acute coronary syndrome (OR 1.07, 95% CI 1.03 to 1.12) in fully adjusted models at time of diabetes diagnosis.ConclusionsMicrovascular and macrovascular diseases are detected in 37%–24% of people with newly diagnosed type 2 diabetes. Pre-diabetes before diagnosis of type 2 diabetes is associated with increased odds of microvascular disease and acute coronary syndrome. Detection of pre-diabetes might represent an opportunity for reducing the burden of microvascular and macrovascular disease through heightened attention to screening for vascular complications. ]]> <![CDATA[Development and validation of an early pregnancy risk score for the prediction of gestational diabetes mellitus in Chinese pregnant women]]> https://www.researchpad.co/article/elastic_article_7271 To develop and validate a set of risk scores for the prediction of gestational diabetes mellitus (GDM) before the 15th gestational week using an established population-based prospective cohort.MethodsFrom October 2010 to August 2012, 19 331 eligible pregnant women were registered in the three-tiered antenatal care network in Tianjin, China, to receive their antenatal care and a two-step GDM screening. The whole dataset was randomly divided into a training dataset (for development of the risk score) and a test dataset (for validation of performance of the risk score). Logistic regression was performed to obtain coefficients of selected predictors for GDM in the training dataset. Calibration was estimated using Hosmer-Lemeshow test, while discrimination was checked using area under the receiver operating characteristic curve (AUC) in the test dataset.ResultsIn the training dataset (total=12 887, GDM=979 or 7.6%), two risk scores were developed, one only including predictors collected at the first antenatal care visit for early prediction of GDM, like maternal age, body mass index, height, family history of diabetes, systolic blood pressure, and alanine aminotransferase; and the other also including predictors collected during pregnancy, that is, at the time of GDM screening, like physical activity, sitting time at home, passive smoking, and weight gain, for maximum performance. In the test dataset (total=6444, GDM=506 or 7.9%), the calibrations of both risk scores were acceptable (both p for Hosmer-Lemeshow test >0.25). The AUCs of the first and second risk scores were 0.710 (95% CI: 0.680 to 0.741) and 0.712 (95% CI: 0.682 to 0.743), respectively (p for difference: 0.9273).ConclusionBoth developed risk scores had adequate performance for the prediction of GDM in Chinese pregnant women in Tianjin, China. Further validations are needed to evaluate their performance in other populations and using different methods to identify GDM cases. ]]> <![CDATA[Conditions, pathogenesis, and progression of diabetic kidney disease and early decliner in Japan]]> https://www.researchpad.co/article/N0b672640-5487-4dd2-b8cf-c5b83622cc24 Glomerular filtration rate (GFR) decreases without or prior to the development of albuminuria in many patients with diabetes. Therefore, albuminuria and/or a low GFR in patients with diabetes is referred to as diabetic kidney disease (DKD). A certain proportion of patients with diabetes show a rapid progressive decline in renal function in a unidirectional manner and are termed early decliners. This study aimed to elucidate the prevalence of DKD and early decliners and clarify their risk factors.Research design and methodsThis combination cross-sectional and cohort study included 2385 patients with diabetes from 15 hospitals. We defined DKD as a urinary albumin to creatinine ratio (ACR) ≥30 mg/gCr and/or estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m². We classified patients into four groups based on the presence or absence of albuminuria and a decrease in eGFR to reveal the risk factors for DKD. We also performed a trajectory analysis and specified the prevalence and risk factors of early decliners with sequential eGFR data of 1955 patients in five facilities.ResultsOf our cohort, 52% had DKD. Above all, 12% with a low eGFR but no albuminuria had no traditional risk factors, such as elevated glycated hemoglobin, elevated blood pressure, or diabetic retinopathy in contrast to patients with albuminuria but normal eGFR. Additionally, 14% of our patients were early decliners. Older age, higher basal eGFR, higher ACR, and higher systolic blood pressure were significantly associated with early decliners.ConclusionsThe prevalence of DKD in this cohort was larger than ever reported. By testing eGFR yearly and identifying risk factors in the early phase of diabetes, we can identify patients at high risk of developing end-stage renal disease. ]]> <![CDATA[High prevalence of impaired awareness of hypoglycemia and severe hypoglycemia among people with insulin-treated type 2 diabetes: The Dutch Diabetes Pearl Cohort]]> https://www.researchpad.co/article/Nc5d66784-6dec-41ba-940a-34ffedf215f6 People with type 2 diabetes on insulin are at risk for hypoglycemia. Recurrent hypoglycemia can cause impaired awareness of hypoglycemia (IAH), and increase the risk for severe hypoglycemia. The aim of this study was to assess the prevalence and determinants of self-reported IAH and severe hypoglycemia in a Dutch nationwide cohort of people with insulin-treated type 2 diabetes.Research design and methodsObservational study of The Dutch Diabetes Pearl, a cohort of people with type 2 diabetes treated in primary, secondary and tertiary diabetes care centers. The presence of IAH and the occurrence of severe hypoglycemia in the past year, defined as an event requiring external help to recover, were assessed using the validated Dutch version of the Clarke questionnaire. In addition, clinical variables were collected including age, diabetes duration, hemoglobin A1c, ethnicity and education.Results2350 people with type 2 diabetes on insulin were included: 59.1% men, mean age 61.1±10.4 years, mean diabetes duration 14.8±9.2 years and 79.5% on basal-bolus therapy. A total of 229 patients (9.7%) were classified as having IAH and 742 patients (31.6%) reported severe hypoglycemia. Increased odds for IAH were found with complex insulin regimens and lower odds with having a partner and body mass index ≥30 kg/m2. Severe hypoglycemia was associated with complex insulin regimens, non-Caucasian ethnicity and use of psychoactive drugs, and inversely with metformin use.ConclusionsIn this nationwide cohort, almost one out of ten people with type 2 diabetes on insulin had IAH and >30% had a history of severe hypoglycemia in the past year. ]]> <![CDATA[Association between the triglyceride to high-density lipoprotein cholesterol ratio and the risk of type 2 diabetes mellitus among Chinese elderly: the Beijing Longitudinal Study of Aging]]> https://www.researchpad.co/article/N2929a551-c282-4081-a05d-9e517c293b15 Time-dependent covariates are generally available as longitudinal data were collected periodically in the cohort study. To examine whether time-dependent triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio could predict the future risk of type 2 diabetes mellitus (T2DM) and assess its potential impact on the risk of T2DM incidence.Research design and methodsThis study enrolled 1460 participants without T2DM aged 55 or above in 1992 in the Beijing Longitudinal Study of Aging during 25 years. The questionnaire data were collected in nine surveys from 1992 to 2017. Physical examination and blood laboratory tests including TG and HDL-C concentrations were measured in five surveys. Incident T2DM cases were confirmed via a self-reported history of T2DM or the fasting plasma glucose level.Results119 new cases of T2DM were identified. In the Cox regression analysis with time-dependent TG/HDL-C ratios and covariates, the adjusted hazard ratios (95% confidence interval) of T2DM incidence were 1.90 (1.12 to 3.23), 2.75 (1.58 to 4.80) and 2.84 (1.69 to 4.77), respectively, for those with TG/HDL-C ratios (both TG and HDL-C were expressed in millimole per liter) in the ranges of 0.87–1.30, 1.31–1.74 and ≥1.75, compared with individuals with TG/HDL-C ratios <0.87. The similar results of subdistribution hazard ratios were obtained by performing the Fine-Gray model with time-dependent TG/HDL-C ratios. This positive association and the statistically significant trend with increased risk of T2DM incidence in the three categories of elevated TG/HDL-C ratio was confirmed by multiple sensitivity analyses. Furthermore, the T2DM discriminatory power of TG/HDL-C ratio combining with other risk factors was moderately high.ConclusionsWe found that time-dependent TG/HDL-C ratios were positively associated with the risk of T2DM risk. The elevated TG/HDL-C ratios increased the future risk of T2DM incidence. Lowering the TG/HDL-C ratio could assist in the prevention of diabetes for older adults. ]]> <![CDATA[Effectiveness of a clinic-based randomized controlled intervention for type 2 diabetes management: an innovative model of intensified diabetes management in Mainland China (C-IDM study)]]> https://www.researchpad.co/article/Nb4a5bf6e-b0c9-49fb-8445-b862e5107578 Highly efficient diabetes management programs are needed for tackling diabetes in China. This study aimed to assess the effectiveness of a clinic-based intensified diabetes management model (C-IDM) in Mainland China.Research design and methodsA 2-year clinic-based randomized controlled trial was conducted among patients with type 2 diabetes in Nanjing, China. The C-IDM intervention components comprised four domains (disease targeting management, express referral channel, expert visit, patients’ self-management) and an integrated running system (disease control centers, general hospitals and local clinics). Control group participants received their usual care, while intervention participants received both the C-IDM package and the usual services. The primary outcome variable was change of hemoglobin A1c (HbA1c). Mixed-effects models were used to compute effect estimates and 95% CI with consideration of both individual and cluster-level confounders.ResultsOverall, 1095 of 1143 participants were assessed at study completion. The mean change in HbA1c was significantly greater in the intervention group than in the control group (mean difference (MD)=−0.57, 95% CI −0.79 to –0.36). Similar results were observed for change in body mass index (MD=−0.29, 95% CI −0.49 to –0.10). Participants in the intervention group were more likely to achieve normal HbA1c and body weight compared with their counterparts in control group after adjusting for potentially confounding variables (adjusted OR=1.94, 95% CI 1.35 to 2.81 and 1.79, 95% CI 1.13 to 2.85, respectively).ConclusionsThe C-IDM model is feasible and effective in large-scale management of patients with type 2 diabetes in China. It has public health implications for tackling the burden of diabetes in China.Trial registration numberChiCTR-IOR-15006019. ]]> <![CDATA[Results from NEXT-D: the association of a pre-diabetes-specific health plan and rates of incident diabetes among a national sample of working-age adults]]> https://www.researchpad.co/article/Nd62b3be3-2b72-4ae0-a0bb-fe32c24158cf Pre-diabetes affects one-third of adults in the USA and a subset will progress to type 2 diabetes. Our objective was to determine whether a disease-specific health plan, known as the Diabetes Health Plan (DHP), designed to improve care for persons with pre-diabetes and diabetes also led to lower rates of incident diabetes among adults with pre-diabetes.MethodsWe examined eligibility and claims data from a large payer who offered the DHP to a national sample of employers. We included adult employees and dependents who were continuously covered by the DHP over a 4-year study window. The primary outcome was incident diabetes. We conducted propensity score matching at the employer level to find comparable control employer groups offering standard plans. Using an adjusted logistic regression model at the individual level, we tested the association between DHP employer group status and incident diabetes diagnosis during the 3 years of postbaseline follow-up.FindingsOur analysis included data from 11 965 continuously enrolled adults with pre-diabetes (n=1538 from nine employers offering DHP; n=10 427 from 105 control employers offering standard plans). DHP employees and covered dependents with pre-diabetes had an 8% lower absolute predicted probability of incident diabetes compared with individuals from employer groups offering standard benefit plans (29% predicted probability of incident diabetes for DHP vs 37% for controls, p<0.001).ConclusionsA pre-diabetes-specific health benefit design was associated with lower rates of incident diabetes and represents an area of needed future study. ]]> <![CDATA[Prevalence of diagnosed diabetes in American Indian and Alaska Native adults, 2006–2017]]> https://www.researchpad.co/article/N8edf5d8d-32e0-4da4-8799-d846bda79dd6 The objective of this study was to examine recent trends in diagnosed diabetes prevalence for American Indian and Alaska Native (AI/AN) adults aged 18 years and older in the Indian Health Service (IHS) active clinical population.Research design and methodsData were extracted from the IHS National Data Warehouse for AI/AN adults for each fiscal year from 2006 (n=729 470) through 2017 (n=1 034 814). The prevalence of diagnosed diabetes for each year and the annual percentage change were estimated for adults overall, as well as by sex, age group, and geographic region.ResultsAfter increasing significantly from 2006 to 2013, diabetes prevalence for AI/AN adults in the IHS active clinical population decreased significantly from 2013 to 2017. Prevalence was 14.4% (95% CI 13.9% to 15.0%) in 2006; 15.4% (95% CI 14.8% to 16.0%) in 2013; and 14.6% (95% CI 14.1% to 15.2%) in 2017. Trends for men and women were similar to the overall population, as were those for all age groups. For all geographic regions, prevalence either decreased significantly or leveled off in recent years.ConclusionsDiabetes prevalence in AI/AN adults in the IHS active clinical population has decreased significantly since 2013. While these results cannot be generalized to all AI/AN adults in the USA, this study documents the first known decrease in diabetes prevalence for AI/AN people. ]]> <![CDATA[Effective diabetes complication management is a step toward a carbon-efficient planet: an economic modeling study]]> https://www.researchpad.co/article/N920e36a7-f37a-4bcc-8234-03f81d7f3047 The management of diabetes-related complications accounts for a large share of total carbon dioxide equivalent (CO2e) emissions. We assessed whether improving diabetes control in people with type 2 diabetes reduces CO2e emissions, compared with those with unchanging glycemic control.MethodsUsing the IQVIA Core Diabetes Model, we estimated the impact of maintaining glycated hemoglobin (HbA1c) at 7% (53 mmol/mol) or reducing it by 1% (11 mmol/mol) on total CO2e/patient and CO2e/life-year (LY). Two different cohorts were investigated: those on first-line medical therapy (cohort 1) and those on third-line therapy (cohort 2). CO2e was estimated using cost inputs converted to carbon inputs using the UK National Health Service’s carbon intensity factor. The model was run over a 50-year time horizon, discounting total costs and quality adjusted life years (QALYs) up to 5% and CO2e at 0%.ResultsMaintaining HbA1c at 7% (53 mmol/mol) reduced total CO2e/patient by 18% (1546 kgCO2e/patient) vs 13% (937 kgCO2e/patient) in cohorts 1 and 2, respectively, and led to a reduction in CO2e/LY gain of 15%–20%. Reducing HbA1c by 1% (11 mmol/mol) caused a 12% (cohort 1) and 9% (cohort 2) reduction in CO2e/patient with a CO2e/LY gain reduction of 11%–14%.ConclusionsWhen comparing people with untreated diabetes, maintaining glycemic control at 7% (53 mmol/mol) on a single agent or improving HbA1c by 1% (11 mmol/mol) by the addition of more glucose-lowering treatment was associated with a reduction in carbon emissions. ]]> <![CDATA[Tissue inhibitor matrix metalloproteinase 1 and risk of type 2 diabetes in a Chinese population]]> https://www.researchpad.co/article/N4633802c-6d58-4c45-a057-84c717a1961a The non-invasive enhanced liver fibrosis (ELF) score—comprising tissue inhibitor of matrix metalloproteinases-1 (TIMP1), hyaluronic acid (HA) and amino-terminal propeptide of type III procollagen (PIIINP)—has been shown to accurately predict fibrosis stages among patients with non-alcoholic fatty liver disease (NAFLD). However, no study has examined whether the ELF score or its components would also be predictive of type 2 diabetes, which commonly coexists and shares the same pathogenic abnormalities with NAFLD. Therefore, we prospectively investigated their associations with type 2 diabetes risks for the first time.Research design and methodsThe ELF score was measured among 254 type 2 diabetes cases and 254 age-matched and sex-matched controls nested within the prospective Singapore Chinese Health Study. Cases had hemoglobin A1c (HbA1c) levels <6.5% at blood collection (1999–2004) and reported to have diabetes during follow-up II (2006–2010). Controls had HbA1c levels <6.0% at blood-taking and remained free of diabetes at follow-up II. Multivariable conditional logistic regression models were used to assess the ELF-diabetes association.ResultsHigher TIMP1 levels were associated with increased type 2 diabetes risk, and the OR comparing the highest versus lowest quartiles was 2.56 (95% CI 1.23 to 5.34; p trend=0.035). However, ELF score, PIIINP and HA were not significantly associated with type 2 diabetes risks.ConclusionsHigher TIMP1 levels, but not ELF score, PIIIMP and HA, were associated with increased type 2 diabetes risk in Chinese adults. Our results suggested that elevated TIMP1 levels may contribute to the type 2 diabetes development through pathways other than liver fibrosis. ]]> <![CDATA[Differential Health Care Use, Diabetes-Related Complications, and Mortality Among Five Unique Classes of Patients With Type 2 Diabetes in Singapore: A Latent Class Analysis of 71,125 Patients]]> https://www.researchpad.co/article/Nc38133b7-afa5-474d-86ec-153e1341c6e5

OBJECTIVE

With rising health care costs and finite health care resources, understanding the population needs of different type 2 diabetes mellitus (T2DM) patient subgroups is important. Sparse data exist for the application of population segmentation on health care needs among Asian T2DM patients. We aimed to segment T2DM patients into distinct classes and evaluate their differential health care use, diabetes-related complications, and mortality patterns.

RESEARCH DESIGN AND METHODS

Latent class analysis was conducted on a retrospective cohort of 71,125 T2DM patients. Latent class indicators included patient’s age, ethnicity, comorbidities, and duration of T2DM. Outcomes evaluated included health care use, diabetes-related complications, and 4-year all-cause mortality. The relationship between class membership and outcomes was evaluated with the appropriate regression models.

RESULTS

Five classes of T2DM patients were identified. The prevalence of depression was high among patients in class 3 (younger females with short-to-moderate T2DM duration and high psychiatric and neurological disease burden) and class 5 (older patients with moderate-to-long T2DM duration and high disease burden with end-organ complications). They were the highest tertiary health care users. Class 5 patients had the highest risk of myocardial infarction (hazard ratio [HR] 12.05, 95% CI 10.82–13.42]), end-stage renal disease requiring dialysis initiation (HR 25.81, 95% CI 21.75–30.63), stroke (HR 19.37, 95% CI 16.92–22.17), lower-extremity amputation (HR 12.94, 95% CI 10.90–15.36), and mortality (HR 3.47, 95% CI 3.17–3.80).

CONCLUSIONS

T2DM patients can be segmented into classes with differential health care use and outcomes. Depression screening should be considered for the two identified classes of patients.

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<![CDATA[Early Childhood Antibiotic Treatment for Otitis Media and Other Respiratory Tract Infections Is Associated With Risk of Type 1 Diabetes: A Nationwide Register-Based Study With Sibling Analysis]]> https://www.researchpad.co/article/Nf47d1c43-9444-4eb5-b05b-e70db4cadc2d

OBJECTIVE

The effect of early-life antibiotic treatment on the risk of type 1 diabetes is debated. This study assessed this question, applying a register-based design in children up to age 10 years including a large sibling-control analysis.

RESEARCH DESIGN AND METHODS

All singleton children (n = 797,318) born in Sweden between 1 July 2005 and 30 September 2013 were included and monitored to 31 December 2014. Cox proportional hazards models, adjusted for parental and perinatal characteristics, were applied, and stratified models were used to account for unmeasured confounders shared by siblings.

RESULTS

Type 1 diabetes developed in 1,297 children during the follow-up (median 4.0 years [range 0–8.3]). Prescribed antibiotics in the 1st year of life (23.8%) were associated with an increased risk of type 1 diabetes (adjusted hazard ratio [HR] 1.19 [95% CI 1.05–1.36]), with larger effect estimates among children delivered by cesarean section (P for interaction = 0.016). The association was driven by exposure to antibiotics primarily used for acute otitis media and respiratory tract infections. Further, we found an association of antibiotic prescriptions in pregnancy (22.5%) with type 1 diabetes (adjusted HR 1.15 [95% CI 1.00–1.32]). In general, sibling analysis supported these results, albeit often with statistically nonsignificant associations.

CONCLUSIONS

Dispensed prescription of antibiotics, mainly for acute otitis media and respiratory tract infections, in the 1st year of life is associated with an increased risk of type 1 diabetes before age 10 years, most prominently in children delivered by cesarean section.

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<![CDATA[Patients’ perspectives on the barriers to referral after telescreening for diabetic retinopathy in communities]]> https://www.researchpad.co/article/N53710bed-8bb8-4986-91cd-43f3131c1d72

Objective

To understand the referral completion and explore the associated barriers to the referral after telescreening for diabetic retinopathy (DR) among people with vision-threatening DR (VTDR).

Research design and methods

All participants with VTDR after DR telescreening in the communities completed the self-reported questionnaires to assess referral completion and their perspectives on referral barriers. Sociodemographic characteristics and perceived barriers related to incomplete referrals were identified by conducting univariate analysis and multiple logistic regression model. The final model was then built to predict incomplete referral.

Results

Of the 3362 participants, 46.1% had incomplete referral. Old age and lower education level showed significant association with incomplete referral. Almost all participants had at least one barrier during the referral process. Knowledge-related and attitude-related barriers, including ‘Too old to want any more treatment’, ‘Difficulty in getting time to referral’, ‘No serious illness requiring treatment at present’, ‘My eyes are okay’, ‘Distrust the recommended hospital’ and ‘Have not been diagnosed or treated before’, and logistics-related barrier ‘Mobility or transportation difficulties’ showed significant association with incomplete referral.

Conclusions

The issue of incomplete referral after DR telescreening is serious among individuals with VTDR, particularly in the elder and low education level population. The negativity of knowledge-related and attitude-related factors might be more prominent than logistic barriers in predicting incomplete referral. Therefore, new strategies to improve the compliance with referral assist in optimizing the referral accessibility, and the ongoing educational support to improve the awareness of disease and increase the effectiveness of physician-patient communication.

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<![CDATA[Projected burden of type 2 diabetes mellitus-related complications in Singapore until 2050: a Bayesian evidence synthesis]]> https://www.researchpad.co/article/Na95ecd29-04d0-494a-b1f9-4e34b2fcad23

Objective

We examined the effects of age, gender, and ethnicity on the risk of acute myocardial infarction, stroke, and end-stage renal disease according to type 2 diabetes mellitus status among adults aged 40–79 in Singapore.

Methods

A Bayesian inference framework was used to derive age-specific, gender-specific and ethnicity-specific prevalence of type 2 diabetes mellitus from the 2010 Singapore National Health Survey, and age-standardized gender and ethnicity-specific incidence rates of acute myocardial infarction, stroke and end-stage renal disease from the National Registry of Diseases Office. Population forecasts were used in tandem with incidence rates to project the future chronic disease burden until 2050.

Results

The highest relative risk of acute myocardial infarction was observed in the youngest age group (aged 40–44), with higher relative risk for women (men: 4.3 (2.7–6.4); women: 16.9 (9.3–28.3)). A similar trend was observed for stroke (men: 6.5 (4.2–9.7); women: 10.7 (6.0–17.4)). For end-stage renal disease, the highest relative risk was for men aged 45–50 (11.8 (8.0–16.9)) and women aged 55–60 (16.4 (10.7–24.0)). The annual incidence of acute myocardial infarction is projected to rise from 9300 (in 2019) to 16 400 (in 2050), the number of strokes from 7300 to 12 800, and the number of end-stage renal disease cases from 1700 to 2700.

Conclusions

Type 2 diabetes mellitus was associated with an increased risk of complications and is modulated by age and gender. Prevention and early detection of type 2 diabetes mellitus can reduce the increasing burden of secondary complications.

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<![CDATA[Decreased risk of colorectal cancer among patients with type 2 diabetes receiving Chinese herbal medicine: a population-based cohort study]]> https://www.researchpad.co/article/N3f74612e-03df-4194-858d-fe85eef1a84e

Objectives

Patients with type 2 diabetes have a higher risk of colorectal cancer (CRC), but whether Chinese herbal medicines (CHMs) can reduce this risk is unknown. This study investigated the effect that CHMs have on CRC risk in patients with type 2 diabetes.

Research design and methods

This cohort study used the Taiwanese National Health Insurance Research Database to identify 54 744 patients, newly diagnosed with type 2 diabetes, aged 20–70 years, who were receiving treatment between 1998 and 2007. From this sample, we randomly selected 14 940 CHMs users and 14 940 non-CHMs users, using propensity scores matching. All were followed through 2012 to record CRC incidence. Cox proportional hazards regression was used to compute the hazard ratio (HR) of CRC by CHMs use.

Results

During follow-up, 235 CHMs users and 375 non-CHMs users developed CRC, incidence rates of 1.73% and 2.47% per 1000 person-years, respectively. CHM users had a significantly reduced risk of CRC compared with non-CHM users (adjusted HR=0.71; 95% CI 0.60 to 0.84). The greatest effect was in those receiving CHMs for more than 1 year. Huang-Qin, Xue-Fu-Zhu-Yu-Tang, Shu-Jing-Huo-Xue-Tang, Liu-Wei-Di-Huang-Wan, Ji-Sheng-Shen-Qi-Wan, Gan-Lu-Yin, Shao-Yao-Gan-Cao-Tang and Ban-Xia-Xie-Xin-Tang were significantly associated with lower risk of CRC.

Conclusion

Integrating CHMs into the clinical management of patients with type 2 diabetes may be beneficial in reducing the risk of CRC.

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