Identifying risk for type 2 diabetes in different age cohorts: does one size fit all?

Estimated effects of reductions in processed meat consumption and unprocessed red meat consumption on occurrences of type 2 diabetes, cardiovascular disease, colorectal cancer, and mortality in the USA: a microsimulation study

BACKGROUND

High consumption of processed meat and unprocessed red meat is associated with increased risk of multiple chronic diseases, although there is substantial uncertainty regarding the relationship for unprocessed red meat. We developed a microsimulation model to estimate how reductions in processed meat and unprocessed red meat consumption could affect rates of type 2 diabetes, cardiovascular disease, colorectal cancer, and mortality in the US adult population.

METHODS

We used data from two versions of the US National Health and Nutrition Examination Survey, one conducted during 2015-16 and one conducted during 2017-18, to create a simulated US population. The starting cohort was restricted to respondents aged 18 years or older who were not pregnant and had 2 days of dietary-recall data. First, we used previously developed risk models to estimate the baseline disease risk of an individual. For type 2 diabetes we used a logistic-regression model and for cardiovascular disease and colorectal cancer we used Cox proportional-hazard models. We then multiplied baseline risk by relative risk associated with individual processed meat and unprocessed red meat consumption. Prevented occurrences of type 2 diabetes, cardiovascular disease, colorectal cancer, and mortality were computed by taking the difference between the incidence in the baseline and intervention scenarios. All stages were repeated for ten iterations to correspond to a 10-year time span. Scenarios were reductions of 5%, 10%, 30%, 50%, 75%, and 100% in grams consumed of processed meat, unprocessed red meat, or both. Each scenario was repeated 50 times for uncertainty analysis.

FINDINGS

The total number of individual respondents included in the simulated population was 8665, representing 242 021 876 US adults. 4493 (51·9%) of 8665 individuals were female and 4172 (48·1%) were male; mean age was 49·54 years (SD 18·38). At baseline, weighted mean daily consumption of processed meat was 29·1 g, with a 30% reduction being 8·7 g per day, and of unprocessed red meat was 46·7 g, with a 30% reduction being 14·0 g per day. We estimated that a 30% reduction in processed meat intake alone could lead to 352 900 (95% uncertainty interval 345 500-359 900) fewer occurrences of type 2 diabetes, 92 500 (85 600-99 900) fewer occurrences of cardiovascular disease, 53 300 (51 400-55 000) fewer occurrences of colorectal cancer, and 16 700 (15 300-17 700) fewer all-cause deaths during the 10-year period. A 30% reduction in unprocessed red meat intake alone could lead to 732 600 (725 700-740 400) fewer occurrences of type 2 diabetes, 291 500 (283 900-298 800) fewer occurrences of cardiovascular disease, 32 200 (31 500-32 700) fewer occurrences of colorectal cancer, and 46 100 (45 300-47 200) fewer all-cause deaths during the 10-year period. A 30% reduction in both processed meat and unprocessed red meat intake could lead to 1 073 400 (1 060 100-1 084 700) fewer occurrences of type 2 diabetes, 382 400 (372 100-391 000) fewer occurrences of cardiovascular disease, 84 400 (82 100-86 200) fewer occurrences of colorectal cancer, and 62 200 (60 600-64 400) fewer all-cause deaths during the 10-year period.

INTERPRETATION

Reductions in processed meat consumption could reduce the burden of some chronic diseases in the USA. However, more research is needed to increase certainty in the estimated effects of reducing unprocessed red meat consumption.

FUNDING

The Wellcome Trust.

Identifying risk factors of developing type 2 diabetes from an adult population with initial prediabetes using a Bayesian network

Background

It is known that people with prediabetes increase their risk of developing type 2 diabetes (T2D), which constitutes a global public health concern, and it is associated with other diseases such as cardiovascular disease.

Methods

This study aimed to determine those factors with high influence in the development of T2D once prediabetes has been diagnosed, through a Bayesian network (BN), which can help to prevent T2D. Furthermore, the set of features with the strongest influences on T2D can be determined through the Markov blanket. A BN model for T2D was built from a dataset composed of 12 relevant features of the T2D domain, determining the dependencies and conditional independencies from empirical data in a multivariate context. The structure and parameters were learned with the bnlearn package in R language introducing prior knowledge. The Markov blanket was considered to find those features (variables) which increase the risk of T2D.

Results

The BN model established the different relationships among features (variables). Through inference, a high estimated probability value of T2D was obtained when the body mass index (BMI) was instantiated to obesity value, the glycosylated hemoglobin (HbA1c) to more than 6 value, the fatty liver index (FLI) to more than 60 value, physical activity (PA) to no state, and age to 48-62 state. The features increasing T2D in specific states (warning factors) were ranked.

Conclusion

The feasibility of BNs in epidemiological studies is shown, in particular, when data from T2D risk factors are considered. BNs allow us to order the features which influence the most the development of T2D. The proposed BN model might be used as a general tool for prevention, that is, to improve the prognosis.

Effect of age and sex on the associations between potential modifiable risk factors and both type 2 diabetes and impaired fasting glycaemia among West African adults

Background

Type 2 diabetes mellitus (T2DM) is becoming one of the leading causes of morbidity and mortality worldwide, including among Africans. Knowledge of the association between traditional risk factors and both diabetes and pre-diabetes, and whether these differ by age and sex, is important for designing targeted interventions. However, little is known about these associations for African populations.

Methods

The study used data from WHO STEPS surveys, comprising 15,520 participants (6,774 men and 8,746 women) aged 25–64 years, from 5 different West African countries, namely Burkina Faso (4,711), Benin (3,816), Mali (1,772), Liberia (2,594), and Ghana (2,662). T-test and chi-square tests were used to compare differences in the prevalence of traditional risk factors for both sexes. Multinomial logistic regression was conducted to ascertain the relative risks (RR) and 95% confidence intervals (CI) for both T2DM and impaired fasting glucose (IFG) relating to each risk factor, including obesity [defined by BMI, waist circumference (WC), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR)], high blood pressure (HBP), fruit and vegetable consumption, physical inactivity, alcohol consumption, and smoking. Models for each of these traditional risk factors and interactions with age and sex were fitted.

Results

Factors associated with T2DM and IFG were age, obesity [defined by BMI, WC, WHtR, and WHR], HBP, smoking, physical inactivity, and fruit and vegetable consumption (p < 0.05). Analysis of interaction effects showed few significant differences in associations between risk factors and T2DM according to age or sex. Significant interaction with age was observed for HBP*age and T2DM [RR; 1.20, 95% CI: (1.01, 1.42)) (p = 0.04)], WHtR*age and T2DM [RR; 1.23, 95% CI: (1.06, 1.44) (p = 0.007)] and WHR*age and IFG [RR: 0.79, 95% CI: (0.67, 0.94) (p = 0.006)]. Some interactions with age and sex were observed for the association of alcohol consumption and both IFG and T2DM, but no clear patterns were observed.

Conclusion

The study found that with very few exceptions, associations between traditional risk factors examined and both IFG and T2DM did not vary by age or sex among the West African population. Policies and public health intervention strategies for the prevention of T2DM and IFG should target adults of any age or sex in West Africa.

Cardiovascular risk, fatty liver disease, glucose and insulin curve among prediabetes phenotypes in Peruvian population

Aims

To describe the cardiovascular risks, fatty liver disease, and glucose and insulin curve among prediabetes phenotypes (PPh) in Peruvian population.

Methods

A study was carried out using a secondary database of a series of patients with identified risk factors for diabetes mellitus type 2 in one clinic in Lima, Peru. Patients were divided according with the OGTT in impaired glucose 2h or IGT(Pph1), impaired fasting glucose or IFG(Pph3) or both(Pph2).

Results

259 patients were identified for analysis, 149 of whom had normal OGTT, 94 had prediabetes (36.3%), and 16 diabetes (6.2%). We found that 37(39.4%), 37(39.4%) and 20(21.2%) presented Pph1, Pph-2 and Pph-3 respectively. Most of the cardiovascular risks and hepatic function comparison showed no difference in our study sample groups. However, we found that Pph2 showed significantly higher abnormalities in HDL-c, triglycerides, hepatic steatosis, and HOMA-IR compared with normal OGTT group (p < 0.05). Interestingly, this difference was not seen with the other phenotypes. Also, hepatic steatosis was higher in Pph2 compared to Pph3 (p < 0.05). HOMA-IR was high in Phenotype 2 compared with Phenotype 1. Regarding hepatic steatosis, this was high in all prediabetes phenotypes, however we found this to be of statistical significance in Pph2 compared to Pph3 (p < 0.01).

Conclusions

In general, prediabetes phenotypes show a similar association with cardiovascular risk factors and hepatic steatosis, however, Pph2 show more differences in specific comparisons. We believe that this study is a starting point for further investigation to understand prediabetes in Peruvian population and be able to improve disease risk stratification.

Pancreas Fat, an Early Marker of Metabolic Risk? A Magnetic Resonance Study of Chinese and Caucasian Women: TOFI_Asia Study

Objective

Prevalence of type 2 diabetes (T2D) is disproportionately higher in younger outwardly lean Asian Chinese compared to matched Caucasians. Susceptibility to T2D is hypothesised due to dysfunctional adipose tissue expansion resulting in adverse abdominal visceral and organ fat accumulation. Impact on early risk, particularly in individuals characterised by the thin-on-the-outside-fat-on-the-inside (TOFI) phenotype, is undetermined.

Methods

Sixty-eight women [34 Chinese, 34 Caucasian; 18–70 years; body mass index (BMI), 20–45 kg/m2] from the TOFI_Asia study underwent magnetic resonance imaging and spectroscopy to quantify visceral, pancreas, and liver fat. Total body fat was (TBF) assessed by dual-energy x-ray absorptiometry, and fasting blood biomarkers were measured. Ethnic comparisons, conducted using two-sample tests and multivariate regressions adjusted for age, % TBF and ethnicity, identified relationships between abdominal ectopic fat depots with fasting plasma glucose (FPG), insulin resistance (HOMA2-IR), and related metabolic clinical risk markers in all, and within ethnic groups.

Results

Despite being younger and of lower bodyweight, Chinese women in the cohort had similar BMI and % TBF compared to their Caucasian counterparts. Protective high-density lipoprotein cholesterol, total- and high-molecular weight adiponectin were significantly lower, while glucoregulatory glucagon-like peptide-1 and glucagon significantly higher, in Chinese. There were no ethnic differences between % pancreas fat and % liver fat. However, at low BMI, % pancreas and % liver fat were ∼1 and ∼2% higher in Chinese compared to Caucasian women. In all women, % pancreas and visceral adipose tissue had the strongest correlation with FPG, independent of age and % TBF. Percentage (%) pancreas fat and age positively contributed to variance in FPG, whereas % TBF, amylin and C-peptide contributed to IR which was 0.3 units higher in Chinese.

Conclusion

Pancreas fat accumulation may be an early adverse event, in TOFI individuals, with peptides highlighting pancreatic dysfunction as drivers of T2D susceptibility. Follow-up is warranted to explore causality.

Body Mass Index and Birth Weight Improve Polygenic Risk Score for Type 2 Diabetes

One of the major challenges in the post-genomic era is elucidating the genetic basis of human diseases. In recent years, studies have shown that polygenic risk scores (PRS), based on aggregated information from millions of variants across the human genome, can estimate individual risk for common diseases. In practice, the current medical practice still predominantly relies on physiological and clinical indicators to assess personal disease risk. For example, caregivers mark individuals with high body mass index (BMI) as having an increased risk to develop type 2 diabetes (T2D). An important question is whether combining PRS with clinical metrics can increase the power of disease prediction in particular from early life. In this work we examined this question, focusing on T2D. We present here a sex-specific integrated approach that combines PRS with additional measurements and age to define a new risk score. We show that such approach combining adult BMI and PRS achieves considerably better prediction than each of the measures on unrelated Caucasians in the UK Biobank (UKB, n = 290,584). Likewise, integrating PRS with self-reports on birth weight (n = 172,239) and comparative body size at age ten (n = 287,203) also substantially enhance prediction as compared to each of its components. While the integration of PRS with BMI achieved better results as compared to the other measurements, the latter are early-life measurements that can be integrated already at childhood, to allow preemptive intervention for those at high risk to develop T2D. Our integrated approach can be easily generalized to other diseases, with the relevant early-life measurements.

Trends in osteoporosis and mean bone density among type 2 diabetes patients in the US from 2005 to 2014

This study aimed to examine how bone health changed among T2DM patients in the past decade. Continuous National Health and Nutrition Examination Survey (NHANES) data from 2005-2006 to 2013-2014 were analyzed to examine the trends of bone mineral density (BMD) and the prevalence trends of osteoporosis osteopenia among T2DM patients and non-diabetic people aged 40 years and older. The age- and BMI-adjusted mean BMD of the femur neck for the four NHANES cycles decreased linearly in both T2DM patients and non-diabetic people (both Plinear trend ≤ 0.009). Among women with T2DM, the mean BMD in 2013-2014 was significantly lower than that in 2005-2006, even after adjusting for multiple covariates. During 2005-2014, the prevalence of osteoporosis among T2DM patients and non-diabetic people increased but with no significant linear trend (both Plinear trend > 0.05), while the prevalence of osteopenia in the two populations increased linearly (both Plinear trend < 0.04). Age- and BMI-adjusted mean BMD decreased in 2013-2014 in patients with T2DM and non-diabetic people, while the prevalence of osteoporosis and osteopenia increased in both groups.

Regulation of cellular senescence by extracellular matrix during chronic fibrotic diseases

The extracellular matrix (ECM) is a complex network of macromolecules surrounding cells providing structural support and stability to tissues. The understanding of the ECM and the diverse roles it plays in development, homoeostasis and injury have greatly advanced in the last three decades. The ECM is crucial for maintaining tissue homoeostasis but also many pathological conditions arise from aberrant matrix remodelling during ageing. Ageing is characterised as functional decline of tissue over time ultimately leading to tissue dysfunction, and is a risk factor in many diseases including cardiovascular disease, diabetes, cancer, dementia, glaucoma, chronic obstructive pulmonary disease (COPD) and fibrosis. ECM changes are recognised as a major driver of aberrant cell responses. Mesenchymal cells in aged tissue show signs of growth arrest and resistance to apoptosis, which are indicative of cellular senescence. It was recently postulated that cellular senescence contributes to the pathogenesis of chronic fibrotic diseases in the heart, kidney, liver and lung. Senescent cells negatively impact tissue regeneration while creating a pro-inflammatory environment as part of the senescence-associated secretory phenotype (SASP) favouring disease progression. In this review, we explore and summarise the current knowledge around how aberrant ECM potentially influences the senescent phenotype in chronic fibrotic diseases. Lastly, we will explore the possibility for interventions in the ECM-senescence regulatory pathways for therapeutic potential in chronic fibrotic diseases.

Telomere length in different metabolic categories: Clinical associations and modification potential

IMPACT STATEMENT

Metabolic disorders are known to be associated with accelerated telomere attrition. Their pathophysiological heterogeneity suggests the importance of multiple tests in examining these associations. However, oral glucose tolerance test (OGTT) has rarely been performed in such studies to date. There are few studies aimed at determining leukocyte telomere length (LTL) in different categories of impaired glucose tolerance (IGT), and those that do exist do not take into account the impaired fasting glucose (IFG)/IGT categorization. Therefore, we believe our study, when the OGTT was used, is important to the field. This testing made it possible to determine whether LTLs are associated with glucose levels in different hyperglycemic categories. Our data indicate that relationships between LTLs and IFG/IGT levels are not the same. This distinction can potentially be used in categorization of metabolic disorders and in determining the effectiveness of interventions aimed at treating diabetes and other metabolic abnormalities.

Mining treatment patterns of glucose-lowering medications for type 2 diabetes in the Netherlands

RATIONALE AND OBJECTIVES

Different classes of glucose-lowering medications are used for patients with type 2 diabetes mellitus (T2DM) management. It is unclear how often these medications are prescribed in clinical practice. In this study, we aimed to describe treatment patterns of glucose-lowering medications in patients with T2DM in the Netherlands.

METHODS

We studied a cohort of 73 819 patients with T2DM, aged ≥45 years with a first prescription for oral glucose-lowering medication between 2011 and 2017. We used the NControl database with dispensing data from 800 pharmacies in the Netherlands. Prevalence of each glucose-lowering medication class during 6 years after the index date was calculated. Using SQL Server, we identified stepwise patterns of medication prescription in this population.

FINDINGS

During the study period, prevalence of biguanides (BIGU) decreased from 95.6% to 80.8% and use of sulfonylureas (SU) increased from 27.3% to 42.3%. 55.2% of all patients only received BIGUs, 19.1% of all patients started on BIGUs but switched to BIGU +SU. 13.5% of patients with T2DM initiated insulins, on average 532 days (almost 18 months) after the index date.

CONCLUSIONS

Our findings showed that in the Netherlands, medication treatment in patients with T2DM is mainly consistent with the clinical guidelines in the Netherlands during the study period.

Application of a novel sex independent anthropometric index, termed angle index, in relation to type 2 diabetes: a Trinidadian case-control study

OBJECTIVE

To develop a novel sex independent anthropometric index, termed as angle index, related to type 2 diabetes.

DESIGN

Case-control.

PARTICIPANTS

The study comprised 121 participants and were divided into two groups. One group had no form of diabetes and served as controls (n=50). The other group had the condition of type 2 diabetes (n=71). 31% (n=37) of the subjects were male and 69% (n=84) were female. 62% (n=75) of the subjects were of East Indian ethnicity, 28% (n=34) were of African ethnicity and 10% (n=12) were of mixed ethnicity.

SETTING

Participants of the study were from the island of Trinidad, located in the Caribbean. Patients in the study were selected at random from hospital records.

PRIMARY OUTCOME MEASURE

It was hypothesised that the mean angle index of patients with type 2 diabetes would be higher than the mean angle index of patients without type 2 diabetes.

RESULTS

Patients with type 2 diabetes had a significantly higher angle index value as compared with controls (p<0.001). Angle index was the superior sex independent anthropometric index in relation to type 2 diabetes (area under the curve=0.72; p<0.001) as compared with other sex independent variables. Angle index correlated with glycated haemoglobin (r_s=0.28, p=0.003) and fasting blood glucose (r_s=0.31, p=0.001) levels. Patients with type 2 diabetes were four times more likely to have an angle index greater than 184° (OR 4.2, 95% CI 1.8 to 9.9) as compared with controls.

CONCLUSION

Angle index was a superior sex independent index for discriminating between patients with and without type 2 diabetes, as compared with waist circumference, abdominal volume index, conicity index, blood pressure readings, triglyceride levels and very low-density lipoprotein levels.

A Review of the Impacts of Different Approaches for Diabetes Prevention and a Framework for Making Investment Decisions

This paper selectively reviews the economic research on individual (i.e., diabetes prevention programs and financial rewards for weight loss) and population-wide based diabetes prevention interventions (such as food taxes, nutritional labeling, and worksite wellness programs) that demonstrate a direct reduction in diabetes incidence or improvements in diabetes risk factors such as weight, glucose or glycated hemoglobin. The paper suggests a framework to guide decision makers on how to use the available evidence to determine the optimal allocation of resources across population-wide and individual-based interventions. This framework should also assist in the discussion of what parameters are needed from research to inform decision-making on what might be the optimal mix of strategies to reduce diabetes prevalence.