Time trends in the incidence of clinically diagnosed type 2 diabetes and pre-diabetes in the UK 2009-2018: a retrospective cohort study

A Causal Model for Primary Prevention of Cardiovascular Disease: The Health Economic Model for the Primary Prevention of Cardiovascular Disease

OBJECTIVES

Our objective was to design and develop an open-source model capable of simulating interventions for primary prevention of cardiovascular disease (CVD) that incorporated the cumulative effects of risk factors (eg, cholesterol years or blood-pressure years) to enhance health economic modeling in settings which clinical trials are not possible.

METHODS

We reviewed the literature to design the model structure by selecting the most important causal risk factors for CVD-low-density lipoprotein-cholesterol (LDL-C), systolic blood pressure (SBP), smoking, diabetes, and lipoprotein (a) (Lp(a))-and most common CVDs-myocardial infarction and stroke. The epidemiological basis of the model involves the simulation of risk factor trajectories, which are used to modify CVD risk via causal effect estimates derived from Mendelian randomization. LDL-C, SBP, Lp(a), and smoking all have cumulative impacts on CVD risk, which were incorporated into the health economic model. The data for the model were primarily sourced from the UK Biobank study. We calibrated the model using clinical trial data and validated the model against the observed UK Biobank data. Finally, we performed an example health economic analysis to demonstrate the utility of the model. The model is open source.

RESULTS

The model performed well in all validation tests. It was able to produce interpretable and plausible (consistent with expectations of the existing literature) results from an example health economic analysis.

CONCLUSIONS

We have constructed an open-source health economic model capable of incorporating the cumulative effect of LDL-C (ie, cholesterol years), SBP (SBP-years), Lp(a), and smoking on lifetime CVD risk.

Risk of type 2 diabetes and long-term antibiotic use in childhood: Evidence from the UK Biobank

AIMS

This study aimed to investigate the association between long-term use of antibiotics during childhood and the risk of type 2 diabetes mellitus (T2DM) using a prospective cohort from the UK Biobank.

METHODS

Participants in the UK Biobank who completed the online survey for digestive health were included in this prospective cohort study. A Cox regression model adjusted for sociodemographic characteristics, general health factors, mental health, lifestyle factors, comorbidities, and medication use was used to estimate the hazard ratio (HR) and confidence interval (CI) of the association between long-term use of antibiotics in the childhood and incident T2DM.

RESULTS

The final analyses included 152,992 participants and 22,133 of them received long-term/recurrent antibiotics as children or teenagers. During the follow-up, 3370 and 681 incident T2DM cases occurred in the non-exposed and exposed groups respectively. Long-term use of antibiotics in childhood was associated with an increased risk of T2DM, with an HR of 1.16 (95 % CI, 1.07-1.27) after adjusting for potential confounders. Results in the subgroup analyses and sensitivity analyses were highly consistent with the primary analyses.

CONCLUSIONS

Long-term use of antibiotics in childhood is associated with the risk of T2DM in middle and old age in the UK Biobank population.

Sociodemographic characteristics and longitudinal progression of multimorbidity: A multistate modelling analysis of a large primary care records dataset in England

BACKGROUND

Multimorbidity, characterised by the coexistence of multiple chronic conditions in an individual, is a rising public health concern. While much of the existing research has focused on cross-sectional patterns of multimorbidity, there remains a need to better understand the longitudinal accumulation of diseases. This includes examining the associations between important sociodemographic characteristics and the rate of progression of chronic conditions.

METHODS AND FINDINGS

We utilised electronic primary care records from 13.48 million participants in England, drawn from the Clinical Practice Research Datalink (CPRD Aurum), spanning from 2005 to 2020 with a median follow-up of 4.71 years (IQR: 1.78, 11.28). The study focused on 5 important chronic conditions: cardiovascular disease (CVD), type 2 diabetes (T2D), chronic kidney disease (CKD), heart failure (HF), and mental health (MH) conditions. Key sociodemographic characteristics considered include ethnicity, social and material deprivation, gender, and age. We employed a flexible spline-based parametric multistate model to investigate the associations between these sociodemographic characteristics and the rate of different disease transitions throughout multimorbidity development. Our findings reveal distinct association patterns across different disease transition types. Deprivation, gender, and age generally demonstrated stronger associations with disease diagnosis compared to ethnic group differences. Notably, the impact of these factors tended to attenuate with an increase in the number of preexisting conditions, especially for deprivation, gender, and age. For example, the hazard ratio (HR) (95% CI; p-value) for the association of deprivation with T2D diagnosis (comparing the most deprived quintile to the least deprived) is 1.76 ([1.74, 1.78]; p < 0.001) for those with no preexisting conditions and decreases to 0.95 ([0.75, 1.21]; p = 0.69) with 4 preexisting conditions. Furthermore, the impact of deprivation, gender, and age was typically more pronounced when transitioning from an MH condition. For instance, the HR (95% CI; p-value) for the association of deprivation with T2D diagnosis when transitioning from MH is 2.03 ([1.95, 2.12], p < 0.001), compared to transitions from CVD 1.50 ([1.43, 1.58], p < 0.001), CKD 1.37 ([1.30, 1.44], p < 0.001), and HF 1.55 ([1.34, 1.79], p < 0.001). A primary limitation of our study is that potential diagnostic inaccuracies in primary care records, such as underdiagnosis, overdiagnosis, or ascertainment bias of chronic conditions, could influence our results.

CONCLUSIONS

Our results indicate that early phases of multimorbidity development could warrant increased attention. The potential importance of earlier detection and intervention of chronic conditions is underscored, particularly for MH conditions and higher-risk populations. These insights may have important implications for the management of multimorbidity.

HbA1c-defined prediabetes and progression to type 2 diabetes in Denmark: A population-based study based on routine clinical care laboratory data

AIMS

To estimate the prevalence, incidence, mortality, and risk of progression to type 2 diabetes for individuals with HbA1c-defined prediabetes based on Danish nationwide population-based laboratory databases.

METHODS

We included all HbA1c measurements from general practice and hospitals during 2012 to 2018. We estimated the cumulative incidence of having at least one HbA1c measurement. The prevalence and incidence rates of prediabetes (HbA1c 42-47 mmol/mol) were examined in the adult Danish population. The 5-year cumulative incidence of progression to type 2 diabetes was estimated with death as competing event.

RESULTS

Among 4,979,590 adult Danes, 70.8% (95% CI 70.8-70.9) had at least one HbA1c measurement during 2012 to 2018. The prevalence of prediabetes was 7.1% (95% CI 7.1-7.1) in 2018. The incidence rate was 14.2 (95% CI 14.1-14.3) per 1,000 person-years, with median age 66.9 years (IQR 56.7-75.7) and median HbA1c 43 mmol/mol (IQR 42-44) at prediabetes diagnosis. Within five years, 17.5% (95% CI 17.3-17.7) died and the 5-year cumulative incidence of type 2 diabetes was 21.3% (95% CI 21.1-21.5).

CONCLUSIONS

Out of 100 Danish adults, 1.4 develop prediabetes each year and they can be identified at an early stage in laboratory databases. Within five years, one in five individuals with prediabetes progresses to diabetes and one in six dies.

Temporality of body mass index, blood tests, comorbidities and medication use as early markers for pancreatic ductal adenocarcinoma (PDAC): a nested case-control study

OBJECTIVE

Prior studies identified clinical factors associated with increased risk of pancreatic ductal adenocarcinoma (PDAC). However, little is known regarding their time-varying nature, which could inform earlier diagnosis. This study assessed temporality of body mass index (BMI), blood-based markers, comorbidities and medication use with PDAC risk .

DESIGN

We performed a population-based nested case-control study of 28 137 PDAC cases and 261 219 matched-controls in England. We described the associations of biomarkers with risk of PDAC using fractional polynomials and 5-year time trends using joinpoint regression. Associations with comorbidities and medication use were evaluated using conditional logistic regression.

RESULTS

Risk of PDAC increased with raised HbA1c, liver markers, white blood cell and platelets, while following a U-shaped relationship for BMI and haemoglobin. Five-year trends showed biphasic BMI decrease and HbA1c increase prior to PDAC; early-gradual changes 2-3 years prior, followed by late-rapid changes 1-2 years prior. Liver markers and blood counts (white blood cell, platelets) showed monophasic rapid-increase approximately 1 year prior. Recent diagnosis of pancreatic cyst, pancreatitis, type 2 diabetes and initiation of certain glucose-lowering and acid-regulating therapies were associated with highest risk of PDAC.

CONCLUSION

Risk of PDAC increased with raised HbA1c, liver markers, white blood cell and platelets, while followed a U-shaped relationship for BMI and haemoglobin. BMI and HbA1c derange biphasically approximately 3 years prior while liver markers and blood counts (white blood cell, platelets) derange monophasically approximately 1 year prior to PDAC. Profiling these in combination with their temporality could inform earlier PDAC diagnosis.

Ractopamine residues in meat might reduce the risk of type 2 diabetes

Background: The overall prevalence of diabetes in the world has risen substantially in the past several decades, so have complications and mortalities associated with it. Aim: Prevention strategies for diabetes thus become an urgent public health need for reducing the burden of diabetes. Methods: Ractopamine, a β1/2-adrenergic receptor agonist, has been approved for use in finishing swine, cattle, and turkey in countries where meat exporting brings tremendous economic benefits. This leanness enhancer is recently found to be a full agonist at trace amine-associated receptor 1 also. A thorough literature review was performed to assess possible effects of ractopamine on glucose metabolism. Results: Activating β-adrenoceptor could lead to glucose-lowering effects independent of insulin while activation on trace amine-associated receptor 1 induces an incretin-like signaling on insulin-secreting pancreatic β-cells. Conclusion: Accordingly, it is hypothesized that long-term consuming meat containing ractopamine might lower the risk of type 2 diabetes.

Initiation of antidepressant medication in people with type 2 diabetes living in the UK - a retrospective cohort study

Introduction

Depression is a common comorbidity in people with type 2 diabetes and it is associated with poorer outcomes. There is limited data on the treatments used for depression in this population. The aim of this study was to explore the rates of initiation of antidepressant prescriptions in people with type 2 diabetes in the UK and identify those most at risk of needing such treatment.

Research Design and Methods

This was a retrospective cohort study using data from IQVIA Medical Research Data (IMRD)‐UK data. Data from general practices in IMRD‐UK between January 2008 and December 2017 were used for this study.

Results

The overall rates of antidepressant prescribing were stable over the study period. The rate of initiation of antidepressant medication in people with type 2 diabetes was 22.93 per 1000 person years at risk (PYAR) with a 95%CI 22.48 to 23.39 compared to 16.89 per 1000 PYAR (95%CI 16.77 to 17.01) in an age and gender matched cohort. The risk of being prescribed antidepressant medication with age had a U‐shaped distribution with the lowest risk in the 65–69 age group. The peak age for antidepressant initiation in men and women was 40–44, with a rate in men of 32.78 per 1000 PYAR (95% CI 29.57 to 36.34) and a rate in women of 46.80 per 1000 PYAR (95% CI 41.90 to 52.26). People with type 2 diabetes with in the least deprived quintile had an initiation rate of 19.66 per 1000 PYAR (95%CI 18.67 to 20.70) compared to 27.19 per 1000 PYAR (95%CI 25.50 to 28.93) in the most deprived quintile, with a 32% increase in the risk of starting antidepressant medication (95%CI 1.22 to 1.43).

Conclusions

People with type 2 diabetes were 30% more likely to be started on antidepressant medication than people without type 2 diabetes. Women with type 2 diabetes were 35% more likely than men to be prescribed antidepressants and the risks increased with deprivation and in younger or older adults, with the lowest rates in the 65–69 year age band. The rates of antidepressant prescribing were broadly stable over the 10‐year period in this study. The antidepressant medications prescribed changed slightly over time with sertraline becoming more widely used and fewer prescriptions of citalopram.

Identification of Pre-Diabetic Biomarkers in the Progression of Diabetes Mellitus

Type 2 diabetes mellitus (T2DM) is a major global health issue. The development of T2DM is gradual and preceded by the pre-diabetes mellitus (pre-DM) stage, which often remains undiagnosed. This study aimed to identify novel pre-DM biomarkers in a high-fat diet (HFD)-induced pre-DM mouse model. Male C57BL/6J mice were fed either a chow diet or HFD for 12 weeks. Serum and liver samples were isolated in a time-dependent manner. Semi-quantitative assessment of secretory cytokines was performed by cytokine array analysis, and 13 cytokines were selected for further analysis based on the changes in expression levels in the pre-DM and T2DM stages. HFD-fed mice gained body weight and exhibited high serum lipid, liver enzyme, glucose, and insulin levels during the progression of pre-DM to T2DM. The mRNA expression of inflammatory and lipogenic genes was elevated in HFD-fed mice The mRNA expression of Fc receptor, IgG, low affinity Iib, lectin, galactose binding, soluble 1, vascular cell adhesion molecule 1, insulin-like growth factor binding protein 5, and growth arrest specific 6 was elevated in the pre-DM, which was confirmed by measuring protein levels. Our study identified novel pre-DM biomarkers that may help to delay or prevent the progression of T2DM.

Trends in the diabetes incidence and mortality in India from 1990 to 2019: a joinpoint and age-period-cohort analysis

Introduction

Globally, a metabolic disorder like Diabetes is considered as one of the largest global health issues, as it accounts for the majority of the disease burden and happens to be one of the leading causes of mortality as well as reduced life expectancy across the world. As in 2019, India is home to the second-largest number (77 million) of Diabetic adults and the number of people affected has been increasing rapidly over the years. Termed as "the diabetes capital of the world," with every fifth diabetic in the world being an Indian, there is an urgent need to address many critically significant challenges posed by Diabetes in India, like, increasing prevalence among young people in urban areas, less awareness among people, high cost of disease management, limited healthcare facilities, suboptimal diabetes control etc. In Indian context, not enough attempts have been made to observe and understand the long-term pattern of diabetes incidence and mortality. This study aims to provide deep insights into the recent trends of diabetes incidence and mortality in India from 1990 to 2019.

Materials and methods

This is an observational study based on the most recent data from the Global Burden of Disease (GBD) Study 2019. We extracted numbers, age-specific and age-standardized incidence and mortality rates of diabetes (from 1990 to 2019) from the Global Health Data Exchange. The average annual percentage changes in incidence and mortality were analysed by joinpoint regression analysis; the net age, period, and cohort effects on the incidence and mortality were estimated by age-period-cohort analysis.

Results

During the study period, age-standardized incidence and mortality rates of diabetes in India experienced an upsurge in numbers, the incidence rate increased from 199.14 to 317.02, and consequently, mortality increased from 22.30 to 27.35 per 100,000 population. The joinpoint regression analysis showed that the age-standardized incidence significantly rose by 1.63 % (95 % CI: 1.57 %, 1.69 %) in Indian males and 1.56 % in Indian females (95 % CI: 1.49 %, 1.63 %) from 1990 to 2019. On the other hand, the age-standardized mortality rates rose by 0.77 % (95 % CI: 0.24 %, 1.31 %) in Indian males and 0.57 % (95 % CI: -0.54 %, 1.70 %) in Indian females. For age-specific rates, incidence increased in most age groups, with exception of age groups 5-9, 70-74, 75-79 and 80-84 in male, and age groups 5-9, 75-79 and 80-84 in female. Mortality in male saw a decreasing trend till age group 20-24, whereas in female, the rate decreased till age group 35-39. The age effect on incidence showed no obvious changes with advancing age, but the mortality significantly increased with advancing age; period effect showed that both incidence and mortality increased with advancing time period; cohort effect on diabetes incidence and mortality decreased from earlier birth cohorts to more recent birth cohorts, while incidence showed no material changes from 1975 to 1979 to 2000-2004 birth cohort.

Conclusions

Mortality of diabetes decreased in younger age groups but increased in older age groups; however, Incidence increased in most age groups for both male and female. The net age or period effect showed an unfavourable trend while the net cohort effect presented a favourable trend. Aging was likely to drive a continued increase in the mortality of diabetes. Timely population-level interventions aiming for health education, lifestyle modification with special emphasis on the promotion of physical activity and healthy diet should be conducted, especially for male and earlier birth cohorts at high risk of diabetes.