The relative importance of modifiable potential risk factors of type 2 diabetes: a meta-analysis of two cohorts

Which approach better predicts diabetes: Traditional econometric methods or machine learning? Evidence from a cross-sectional study in South Korea

To prevent chronic disease from getting worse, it is important to detect and predict it at an early stage. Therefore, the accuracy of the prediction is particularly important. To investigate the accuracy of different methods, this study compares the out-of-sample errors of machine learning algorithms and traditional econometric methods in predicting diabetes. The object of prediction in this study is fasting blood glucose, and the machine learning algorithms used are stepwise selection, bagging, random forests and support vector machine (SVM). In addition, we demonstrate the linear combination of above machine learning algorithms in this study. The findings indicate that the combined model outperforms both traditional econometric models and individual machine learning algorithms. However, the predictive performance of individual machine learning models does not consistently surpass that of traditional econometric approaches. Based on the data characteristics analyzed in this study, a possible explanation for this finding is that traditional econometric methods may exhibit superior performance in linear data prediction. Finally, the analysis of variable importance suggests that medical indicators and physical condition may play a more significant role in determining fasting blood glucose compared to hereditary factors. To further validate our results, we applied the same methodology to predict hypertension using the same dataset. The findings similarly indicated that the predictive ability of individual machine learning algorithms does not always surpass that of traditional econometric models. And a linear combination of the four machine learning algorithms enhances the predictive accuracy for hypertension.

Enhancing type 2 diabetes mellitus prediction by integrating metabolomics and tree-based boosting approaches

Background

Type 2 diabetes mellitus (T2DM) is a global health problem characterized by insulin resistance and hyperglycemia. Early detection and accurate prediction of T2DM is crucial for effective management and prevention. This study explores the integration of machine learning (ML) and explainable artificial intelligence (XAI) approaches based on metabolomics panel data to identify biomarkers and develop predictive models for T2DM.

Methods

Metabolomics data from T2DM (n = 31) and healthy controls (n = 34) were analyzed for biomarker discovery (mostly amino acids, fatty acids, and purines) and T2DM prediction. Feature selection was performed using the least absolute shrinkage and selection operator (LASSO) regression to enhance the model's accuracy and interpretability. Advanced three tree-based ML algorithms (KTBoost: Kernel-Tree Boosting; XGBoost: eXtreme Gradient Boosting; NGBoost: Natural Gradient Boosting) were employed to predict T2DM using these biomarkers. The SHapley Additive exPlanations (SHAP) method was used to explain the effects of metabolomics biomarkers on the prediction of the model.

Results

The study identified multiple metabolites associated with T2DM, where LASSO feature selection highlighted important biomarkers. KTBoost [Accuracy: 0.938; CI: (0.880-0.997), Sensitivity: 0.971; CI: (0.847-0.999), Area under the Curve (AUC): 0.965; CI: (0.937-0.994)] demonstrated its effectiveness in using complex metabolomics data for T2DM prediction and achieved better performance than other models. According to KTBoost's SHAP, high levels of phenylactate (pla) and taurine metabolites, as well as low concentrations of cysteine, laspartate, and lcysteate, are strongly associated with the presence of T2DM.

Conclusion

The integration of metabolomics profiling and XAI offers a promising approach to predicting T2DM. The use of tree-based algorithms, in particular KTBoost, provides a robust framework for analyzing complex datasets and improves the prediction accuracy of T2DM onset. Future research should focus on validating these biomarkers and models in larger, more diverse populations to solidify their clinical utility.

National burden and risk factors of diabetes mellitus in China from 1990 to 2021: Results from the Global Burden of Disease study 2021

BACKGROUND

In recent years, the prevalence and mortality rates of diabetes have been rising continuously, posing a significant threat to public health and placing a heavy burden on the population. This study was conducted to describe and analyze the burden of diabetes in China from 1990 to 2021 and its attributable risk factors.

METHODS

Utilizing data from the Global Burden of Disease Study 2021, we analyzed the incidence, prevalence, and disability-adjusted life years (DALYs) of type 1 diabetes (T1DM) and type 2 diabetes (T2DM) in China from 1990 to 2021. We extracted sex- and age-specific data on diabetes, focusing on DALYs, years lived with disability, and years of life lost. Bayesian meta-regression and spatiotemporal Gaussian process regression were used to estimate disease parameters. Age-standardized rates (ASRs) and estimated annual percentage changes (EAPC) were calculated using direct standardization and log-linear regression. The population-attributable fractions were also determined for each risk factor.

RESULTS

In 2021, the absolute number of incident diabetes mellitus (DM) cases was estimated at 4003543.82, including 32 000 T1DM and 3971486.24 T2DM cases. The ASRs were 244.57 for DM, 2.67 for T1DM, and 241.9 for T2DM (per 100 000 population). The absolute number of prevalent DM cases was 117288553.93, including 1442775.09 T1DM and 115845778.84 T2DM cases. The ASRs were 6142.29 for DM, 86.78 for T1DM, and 6055.51 for T2DM (per 100 000 population). In 2021, there were 178475.73 deaths caused by DM, with an ASR of mortality of 8.98 per 100 000 population. The DALYs due to DM in 2021 were 11713613.86, with an ASR of 585.43 per 100 000 population and an EAPC of 0.57. This increase can be attributed to several factors, including high body mass index, air pollution, and dietary habits.

CONCLUSIONS

The burden of diabetes is considerable, with high prevalence and incidence rates, highlighting the urgent need for public health interventions. Addressing factors like high fasting plasma glucose, body mass index, air pollution, and dietary risks through effective interventions is critical.

Identifying subtypes of type 2 diabetes mellitus with machine learning: development, internal validation, prognostic validation and medication burden in linked electronic health records in 420 448 individuals

INTRODUCTION

None of the studies of type 2 diabetes (T2D) subtyping to date have used linked population-level data for incident and prevalent T2D, incorporating a diverse set of variables, explainable methods for cluster characterization, or adhered to an established framework. We aimed to develop and validate machine learning (ML)-informed subtypes for type 2 diabetes mellitus (T2D) using nationally representative data.

RESEARCH DESIGN AND METHODS

In population-based electronic health records (2006-2020; Clinical Practice Research Datalink) in individuals ≥18 years with incident T2D (n=420 448), we included factors (n=3787), including demography, history, examination, biomarkers and medications. Using a published framework, we identified subtypes through nine unsupervised ML methods (K-means, K-means++, K-mode, K-prototype, mini-batch, agglomerative hierarchical clustering, Birch, Gaussian mixture models, and consensus clustering). We characterized clusters using intracluster distributions and explainable artificial intelligence (AI) techniques. We evaluated subtypes for (1) internal validity (within dataset; across methods); (2) prognostic validity (prediction for 5-year all-cause mortality, hospitalization and new chronic diseases); and (3) medication burden.

RESULTS

Development: We identified four T2D subtypes: metabolic, early onset, late onset and cardiometabolic. Internal validity: Subtypes were predicted with high accuracy (F1 score >0.98). Prognostic validity: 5-year all-cause mortality, hospitalization, new chronic disease incidence and medication burden differed across T2D subtypes. Compared with the metabolic subtype, 5-year risks of mortality and hospitalization in incident T2D were highest in late-onset subtype (HR 1.95, 1.85-2.05 and 1.66, 1.58-1.75) and lowest in early-onset subtype (1.18, 1.11-1.27 and 0.85, 0.80-0.90). Incidence of chronic diseases was highest in late-onset subtype and lowest in early-onset subtype. Medications: Compared with the metabolic subtype, after adjusting for age, sex, and pre-T2D medications, late-onset subtype (1.31, 1.28-1.35) and early-onset subtype (0.83, 0.81-0.85) were most and least likely, respectively, to be prescribed medications within 5 years following T2D onset.

CONCLUSIONS

In the largest study using ML to date in incident T2D, we identified four distinct subtypes, with potential future implications for etiology, therapeutics, and risk prediction.

A review of dairy food intake for improving health among black adults in the US

The adult life stage encompasses a range of new experiences, opportunities, and responsibilities that impact health and well-being. During this life stage, health disparities continue to increase for Black Americans, with Black adults having a disproportionate burden of obesity, chronic diseases, comorbidities, and worse treatment outcomes compared to their White peers. While many of the underlying factors for these disparities can be linked to longstanding sociopolitical factors such as systemic racism, food insecurity, and poor access to healthcare, there are also several modifiable risk factors that are known to significantly impact health outcomes, such as improving diet quality, increasing physical activity, and not smoking. Of all the modifiable risk factors known to impact health, improving dietary habits is the factor most consistently associated with better outcomes for body weight and chronic disease. Of the major food groups recommended by the 2020-2025 Dietary Guidelines for Americans (DGA) for achieving healthier dietary patterns, dairy foods have a nutrient profile which matches most closely to what Black Americans are inadequately consuming (e.g., vitamin A, vitamin D, calcium, magnesium). However, Black adults tend to consume less than half the recommended daily servings of dairy foods, in part, due to issues with lactose intolerance, making higher intake of dairy foods an ideal target for improving diet quality and health in this population. This review examines the current body of evidence exploring the links between dairy intake, obesity, cardiometabolic disease risk, chronic kidney disease, and the most common types of cancer, with a special focus on health and disparities among Black adults. Overall, the evidence from most systematic reviews and/or meta-analyses published in the last decade on dairy intake and health outcomes has been conducted on White populations and largely excluded research on Black populations. The findings from this extensive body of research indicate that when teamed with an energy-restricted diet, meeting or exceeding the DGA recommended 3 daily servings of dairy foods is associated with better body weight and composition outcomes and lower rates of most common chronic diseases than lower intake (<2 servings per day). In addition to the number of daily servings consumed, the specific types (e.g., milk, yogurt, cheese) and subtypes (e.g., low-fat, fermented, fortified) consumed have also been shown to play major roles in how these foods impact health. For example, higher intake of fermented dairy foods (e.g., yogurt) and vitamin D fortified dairy products appear to have the most protective effects for reducing chronic disease risk. Along with lactose-free milk and cheese, yogurt is also generally low in lactose, making it an excellent option for individuals with lactose intolerance, who are trying to meet the DGA recommendations for dairy food intake.

Sex-specific associations between skeletal muscle mass and incident diabetes: A population-based cohort study

AIMS

To investigate the sex-specific associations between predicted skeletal muscle mass index (pSMI) and incident type 2 diabetes in a retrospective longitudinal cohort of Chinese men and women.

MATERIALS AND METHODS

We enrolled Chinese adults without diabetes at baseline from WATCH (West chinA adulT health CoHort), a large health check-up-based database. We calculated pSMI to estimate skeletal muscular mass, and measured blood glucose variables and assessed self-reported history to identify new-onset diabetes. The nonlinear association between pSMI and incident type 2 diabetes was modelled using the penalized spline method. The piecewise association was estimated using segmented linear splines in weighted Cox proportional hazards regression models.

RESULTS

Of 47 885 adults (53.2% women) with a median age of 40 years, 1836 developed type 2 diabetes after a 5-year median follow-up. In women, higher pSMI was associated with a lower risk of incident type 2 diabetes (Pnonlinearity  = 0.09, hazard ratio [HR] per standard deviation increment in pSMI: 0.79 [95% confidence interval {CI} 0.68, 0.91]). A nonlinear association of pSMI with incident type 2 diabetes was detected in men (Pnonlinearity  < 0.001). In men with pSMI lower than 8.1, higher pSMI was associated with a lower risk of incident type 2 diabetes (HR 0.58 [95% CI 0.40, 0.84]), whereas pSMI was not significantly associated with incident diabetes in men with pSMI equal to or greater than 8.1 (HR 1.08 [95% CI 0.93, 1.25]).

CONCLUSIONS

In females, a larger muscular mass is associated with a lower risk of type 2 diabetes. For males, this association is significant only among those with diminished muscle mass.

The Description and Prediction of Incidence, Prevalence, Mortality, Disability-Adjusted Life Years Cases, and Corresponding Age-Standardized Rates for Global Diabetes

OBJECTIVE

Diabetes is a life-long disease that poses a serious threat to safety and health. We aimed to assess the disease burden attributable to diabetes globally and by different subgroups, and to predict future disease burden using statistical models.

METHODS

This study was divided into three stages. Firstly, we evaluated the disease burden attributable to diabetes globally and by different subgroups in 2019. Second, we assessed the trends from 1990 to 2019. We estimated the annual percentage change of disease burden by applying a linear regression model. Finally, the age-period-cohort model was used to predict the disease burden from 2020 to 2044. Sensitivity analysis was performed with time-series models.

RESULTS

In 2019, the number of incidence cases of diabetes globally was 22239396 (95% uncertainty interval (UI): 20599519-24058945). The number of prevalence cases was 459875371 (95% UI 423474244-497980624) the number of deaths cases was 1551170 (95% UI 1445555-1650675) and the number of disability-adjusted life years cases was 70880155 (95% UI 59707574-84174005). The disease burden was lower in females than males and increased with age. The disease burden associated with type 2 diabetes mellitus was greater than that with type 1; the burden also varied across different socio-demographic index regions and different countries. The global disease burden of diabetes increased significantly over the past 30 years and will continue to increase in the future.

CONCLUSION

The disease burden of diabetes contributed significantly to the global disease burden. It is important to improve treatment and diagnosis to halt the growth in disease burden.

Study protocol for an epidemiological study 'Multimorbidity - identifying the most burdensome patterns, risk factors and potentials to reduce future burden (MOLTO)' based on the Finnish health examination surveys and the ongoing register-based follow-up

INTRODUCTION

Multimorbidity, defined as the co-occurrence of two or more long-term medical conditions, is an increasing public health concern worldwide causing enormous burden to individuals, healthcare systems and societies. The most effective way of decreasing the burden caused by multimorbidity is to find tools for its successful prevention but gaps in research evidence limit capacities to develop prevention strategies. The aim of the MOLTO study (Multimorbidity - identifying the most burdensome patterns, risk factors and potentials to reduce future burden) is to provide novel evidence required for cost-effective prevention of multimorbidity by defining the multimorbidity patterns causing the greatest burden at the population level, by examining their risk and protective factors and by estimating the potentials to reduce the future burden.

METHODS AND ANALYSIS

The MOLTO study is based on the data from the Finnish population-based cross-sectional (FINRISK 2002-2012, FinHealth 2017 the Migrant Health and Well-being Study 2010-2012) and longitudinal (Health 2000/2011) health examination surveys with individual-level link to administrative health registers, allowing register-based follow-up for the study participants. Both cross-sectional and longitudinal study designs will be used. Multimorbidity patterns will be defined using latent class analysis. The burden caused by multimorbidity as well as risk and protective factors for multimorbidity will be analysed by survival analysis methods such as Cox proportional hazards and Poisson regression models.

ETHICS AND DISSEMINATION

The survey data have been collected following the legislation at the time of the survey. The ethics committee of the Hospital District of Helsinki and Uusimaa has approved the data collection and register linkages for each survey. The results will be published as peer-reviewed scientific publications.

Changes in the Leptin to Adiponectin Ratio Are Proportional to Weight Loss After Meal Replacement in Adults With Severe Obesity

Hypocaloric diets are known to induce changes in adipokine secretion, but the influence of a low energy liquid diet (LELD) on the leptin: adiponectin ratio (LAR), a measure of insulin resistance and cardiovascular risk, has not previously been investigated in patients with severe obesity. We conducted a prospective, single-center cohort study of adults with severe obesity (defined as body mass index (BMI) ≥40 kgm−2, or ≥35 kgm−2 with co-morbidities) who completed a 24-week milk-based LELD. We measured leptin, adiponectin and LAR at the start and on completion of the programme. Of 120 patients who started, 52 (43.3 %) completed the programme. Their mean age was 50.3 ± 11.2 (range 18–74) years, 29 (55.8 %) were female and 20 (38.5 %) had type 2 diabetes mellitus (T2DM). Weight decreased from 148.2 ± 39.6 to 125.4 ± 34.8 kg and BMI decreased from 52.4 ± 11.1 to 44.3 ± 9.8 kgm−2, respectively (all p &lt; 0.001). In patients with T2DM, HbA1c decreased from 60.0 ± 17.4 to 47.5 ± 15.5 mmol/mol (p &lt; 0.001). Leptin decreased (from 87.2 [48.6, 132.7] to 39.1 [21.0, 76.4] ng/ml) and adiponectin increased (from 5.6 [4.5, 7.5] to 7.1 [5.5, 8.5] μg/ml), with a reduction in LAR from 15 [8.4, 22.4] to 5.7 [3.0, 9.1] ng/μg (all p &lt; 0.001), indicating decreased insulin resistance. The percentage weight lost was associated with the percentage reduction in LAR (ß = 2.9 [1.7, 4.1], p &lt; 0.001) and this association was stronger in patients with T2DM. Patients with severe obesity who completed a milk-based LELD had a substantial reduction in LAR, consistent with decreased insulin resistance and cardiovascular risk, proportional to weight loss.

Prediabetes, type 2 diabetes mellitus and risk of Parkinson's disease: A population-based cohort study

BACKGROUND

Association of type 2 diabetes mellitus (T2D) with subsequent Parkinson's disease (PD) has supported the link between glucose metabolism and PD. We assessed the risk of PD not only in T2D but also in prediabetes.

METHODS

We conducted a retrospective cohort study of the population attended in primary care centres of the Catalan Health Institute in Catalonia between 2006 and 2018. The data were obtained from the Information System for Research in Primary Care (SIDIAP). We created a cohort of T2D and prediabetes patients (HbA1c ≥ 5.7-6.4% without antidiabetic drugs or previous T2D diagnosis) and compared to a reference cohort. The outcome was PD diagnosis and we excluded PD before or during the first year of follow-up. We used multivariate Cox regression models to calculate hazard ratios (HR) and 95% confidence intervals (95%CI). We excluded subjects with atypical and secondary parkinsonisms.

RESULTS

The exposed cohorts comprised of 281.153 patients with T2D and 266.379 with prediabetes and a reference cohort of 2.556.928 subjects. T2D and prediabetes were associated with higher risk of PD (HRadjusted 1.19, 95%CI 1.13-1.25, and 1.07, 1.00-1.14; respectively). In analyses stratified by sex, prediabetes was only associated with PD risk in women (1.12, 1.03-1.22 vs. 1.01, 0.99-1.10 in men). When analysis was stratified by age, T2D and prediabetes were associated with a greater PD risk both in women (2.36, 1.96-2.84 and 2.10, 1.70-2.59 respectively) and men (1.74, 1.52-2.00 and 1.90, 1.57-2.30 respectively) below 65 years-old.

CONCLUSIONS

We report for the first time that prediabetes increases the odds of subsequent PD and replicate the association with established T2D. Both associations predominate in women and young individuals.

A Smartphone App (TRIANGLE) to Change Cardiometabolic Risk Behaviors in Women Following Gestational Diabetes Mellitus: Intervention Mapping Approach

BACKGROUND

Gestational diabetes mellitus (GDM) is the most common complication during pregnancy and is associated with an increased risk for the development of cardiometabolic diseases. Behavioral interventions can reduce this risk, but current solutions insufficiently address the requirements for such a program. The systematic development of a scalable mobile health (mHealth) promotion program for mothers during the first years post-GDM may contribute to solving this problem.

OBJECTIVE

The aim of this project was to systematically plan and develop a theory- and evidence-based mHealth intervention to change cardiometabolic risk behaviors in women during the first 5 years post-GDM that meets women's expected standards of commercial health apps.

METHODS

The intervention mapping steps 1 to 4 structured the systematic planning and development of the mHealth program described in this paper. Steps 1 and 2 led to a theory- and evidence-based logic model of change for cardiometabolic health. Based on this model, the prevention program was designed (step 3) and produced (step 4) in cooperation with industrial partners to ensure a high technological standard of the resulting smartphone app for the iPhone (Apple Inc). Step 4 included a user study with women during the first 5 years post-GDM once a beta version of the app ("TRIANGLE") was available. The user study comprised 2 test rounds of 1 week (n=5) and 4 weeks (n=6), respectively. The tests included validated questionnaires on user acceptance, user logs, and think-alouds with semistructured interviews.

RESULTS

The novel TRIANGLE app is among the first self-paced smartphone apps for individual habit change in the 3 lifestyle areas of physical activity, nutrition, and psychosocial well-being. The 3 core features-a challenge system, human coaching, and a library-address 11 behavioral determinants with 39 behavior change methods to support lifestyle changes. Participants in the user study showed a high acceptance, high perceived quality, and high perceived impact of the TRIANGLE app on their health behaviors. Participants tested the app regularly, used it intuitively, and suggested improvements. We then adapted the TRIANGLE app according to the insights from the user study before the full TRIANGLE program production.

CONCLUSIONS

The intervention mapping approach was feasible to plan and develop an innovative and scalable smartphone solution for women during the first 5 years post-GDM. The resulting TRIANGLE intervention has the potential to support behavior change for cardiometabolic disease prevention. However, the app needs further refinement and testing in clinical trials. Intervention mapping steps 5 (implementation plan) and 6 (evaluation plan) may support the integration of the TRIANGLE intervention into routine care.

TRIAL REGISTRATION

German Clinical Trials Register DRKS00012736; https://www.drks.de/DRKS00012736.

The leptin to adiponectin ratio (LAR) is reduced by sleeve gastrectomy in adults with severe obesity: a prospective cohort study

Bariatric surgery is known to reduce leptin and increase adiponectin levels, but the influence of sleeve gastrectomy on the leptin: adiponectin ratio (LAR), a measure of insulin sensitivity and cardiovascular risk, has not previously been described. We sought to determine the influence of sleeve gastrectomy on LAR in adults with severe obesity.In a single centre prospective cohort study of adults undergoing laparoscopic sleeve gastrectomy over a four-month period in our unit, we measured LAR preoperatively and 12 months after surgery. Of 22 patients undergoing sleeve gastrectomy, 17 (12 females, 12 with type 2 diabetes) had follow-up LAR measured at 12.1 ± 1 months. Mean body weight decreased from 130.6 ± 30.8 kg to 97.6 ± 21.6 kg, body mass index (BMI) from 46.9 ± 7.8 to 35.3 ± 7.2 kg m^-2 and excess body weight from 87.5 ± 31.3 to 41.3 ± 28.8% (all p < 0.001). The reduction in leptin from 40.7 ± 24.9 to 30.9 ± 30.5 ng/ml was not significant (p = 0.11), but adiponectin increased from 4.49 ± 1.6 to 8.93 ± 6.36 µg/ml (p = 0.005) and LAR decreased from 8.89 ± 4.8 to 5.26 ± 6.52 ng/µg (p = 0.001), equivalent to a 70.9% increase in insulin sensitivity. The correlation with the amount of weight lost was stronger for LAR than it was for leptin or adiponectin alone. In this single-centre, interventional prospective cohort, patients undergoing laparoscopic sleeve gastrectomy had a substantial reduction in their LAR after 12 months which was proportional to the amount of weight lost. This may indicate an improvement in insulin sensitivity and a reduction in cardiovascular risk.

Risk and population attributable fraction of metabolic syndrome and impaired fasting glucose for the incidence of type 2 diabetes mellitus among middle-aged Japanese individuals: Aichi Worker's Cohort Study

AIMS/INTRODUCTION

The Japanese government started a nationwide screening program for metabolic syndrome (MetS) to prevent cardiovascular diseases and diabetes in 2008. Although impaired fasting glucose (IFG) is a strong predictor for type 2 diabetes mellitus, the program does not follow up IFG in non-MetS individuals. This study aimed to examine the risk and the population attributable fraction (PAF) of MetS and IFG for incidence of type 2 diabetes mellitus.

MATERIALS AND METHODS

Japanese workers (3,417 men and 714 women) aged 40-64 years without a history of diabetes were prospectively followed. MetS was defined as either abdominal obesity plus two or more metabolic risk factors, or being overweight in the case of normal waist circumference plus three or more metabolic risk factors. IFG was defined as fasting blood glucose 100-125 mg/dL.

RESULTS

During a mean 6.3 years, 240 type 2 diabetes mellitus cases were identified. Compared with those without MetS and IFG, the multivariable-adjusted hazard ratios (95% confidence interval) of non-MetS individuals with IFG, MetS individuals without IFG and MetS individuals with IFG for type 2 diabetes mellitus were 4.9 (3.4-7.1), 2.4 (1.6-3.5) and 8.3 (5.9-11.5), respectively. The corresponding PAFs for type 2 diabetes mellitus incidence were 15.6, 9.1 and 29.7%, respectively.

CONCLUSIONS

IFG represented a higher risk and PAF than MetS for type 2 diabetes mellitus incidence in middle-aged Japanese individuals. The coexistence of MetS and IFG showed the highest risk and PAF for type 2 diabetes mellitus incidence. The current Japanese MetS screening program should be reconsidered to follow up non-MetS individuals with IFG.

Intentional weight loss as a predictor of type 2 diabetes occurrence in a general adult population

INTRODUCTION

Observational and intervention studies have verified that weight loss predicts a reduced type 2 diabetes (T2D) risk. At the population level, knowledge on the prediction of self-report intentional weight loss (IWL) on T2D incidence is, however, sparse. We studied the prediction of self-report IWL on T2D incidence during a 15-year follow-up in a general adult population.

RESEARCH DESIGN AND METHODS

The study sample from the representative Finnish Health 2000 Survey comprised 4270 individuals, aged 30-69 years. IWL was determined with questions concerning dieting attempts and weight loss during the year prior to baseline. Incident T2D cases during a 15-year follow-up were drawn from national health registers. The strength of the association between IWL and T2D incidence was estimated with the Cox model.

RESULTS

During the follow-up, 417 incident cases of T2D occurred. IWL predicted an increased risk of T2D incidence (HR 1.44; 95% CI 1.11 to 1.87, p=0.008) in a multivariable model. In interaction analyses comparing individuals with and without IWL, a suggestively elevated risk emerged in men, the younger age group, among less-educated people and in individuals with unfavorable values in several lifestyle factors.

CONCLUSIONS

Self-report IWL may predict an increased risk of T2D in long-term, probably due to self-implemented IWL tending to fail. The initial prevention of weight gain and support for weight maintenance after weight loss deserve greater emphasis in order to prevent T2D.

How are frames generated? Insights from the industry lobby against the sugar tax in Ireland

There is a causal link between the consumption of ultra-processed foods and a range of non-communicable diseases (NCDs) such as obesity, type 2 diabetes and cancers. Despite this, no country in the world has reduced its obesity levels because the factors that drive obesity continue unchanged (Swinburn et al., 2019). One systemic driver is corporate influence on the public policy process. The world's largest food and beverage manufacturers engage public relations firms to create a narrative which speaks of corporate cooperation with public health policy, while simultaneously influencing policy making in ways that are favorable to industry. We sought to examine framing as a key strategy in the corporate political activity of food industry actors attempting to resist the introduction of a public health policy. Specifically, we analyzed industry submissions for an Irish government consultation for the proposed introduction of a sugar sweetened beverage (SSB) tax in 2018. We describe how a food product like sugar is framed positively by corporate actors who rely on it as their principal ingredient. Sugar is a good focus from a framing perspective because it is currently undergoing recalibration in the public's imagination - from a benign, nourishing treat in its heyday to a dangerous 'substance' that can contribute to premature mortality. Framing is already well established as a corporate political activity (CPA) to influence public policy (Shelton et al., 2017; Nixon et al., 2015; Darmon et al., 2008). Our research expands this understanding by uncovering four underlying mechanisms used to generate frames - dichotomizing, contesting, equating and cropping. Recognizing these mechanisms could help policy makers, public health professionals and business ethicists to deconstruct any given frame that becomes dominant in corporate discourse, such as 'personal responsibility', 'inadequate exercise', 'freedom' and so on. These mechanisms may also apply to other industries such as alcohol, fossil fuels and tobacco, where hazards from interference in public health strategies are a concern.

Type-2 diabetes mellitus in schizophrenia: Increased prevalence and major risk factor of excess mortality in a naturalistic 7-year follow-up

Objective

Physical co-morbidity including type 2 diabetes mellitus is more prevalent in patients with schizophrenia compared to the general population. However, there is little consistent evidence that co-morbidity with diabetes mellitus and/or other diseases leads to excess mortality in schizophrenia. Thus, we investigated whether co-morbidity with diabetes and other somatic diseases is increased in schizophrenics, and if these are equally or more relevant predictors of mortality in schizophrenia than in age- and gender-matched hospitalised controls.

Methods

During 2000–2007, 679 patients with schizophrenia were admitted to University Hospital Birmingham NHS Trust. Co-morbidities were compared with 88,778 age- and gender group-matched hospital controls. Predictors of mortality were identified using forward Cox regression models.

Results

The prevalence of type 2 diabetes mellitus was increased in schizophrenia compared to hospitalised controls (11.3% versus 6.3%). The initial prevalence of type 2 diabetes mellitus was significantly higher in the 100 later deceased schizophrenic patients (24.0%) than in those 579 surviving over 7 years (9.2%). Predictors of mortality in schizophrenia were found to be age (relative risk [RR] = 1.1/year), type 2 diabetes mellitus (RR = 2.2), pneumonia (RR = 2.7), heart failure (RR = 2.9) and chronic renal failure (RR = 3.2). The impact of diabetes mellitus on mortality was significantly higher in schizophrenia than in hospital controls (RR = 2.2 versus RR = 1.1). In agreement, deceased schizophrenics had significantly suffered more diabetes mellitus than deceased controls (24.0 versus 10.5%). The relative risks of mortality for other disorders and their prevalence in later deceased subjects did not significantly differ between schizophrenia and controls.

Conclusion

Schizophrenics have more and additionally suffer more from diabetes: co-morbidity with diabetes mellitus is increased in schizophrenia in comparison with hospital controls; type 2 diabetes mellitus causes significant excess mortality in schizophrenia. Thus, monitoring for and prevention of type 2 diabetes mellitus is of utmost relevance in hospitalised patients with schizophrenia.

Genetic Risk, a Healthy Lifestyle, and Type 2 Diabetes: the Dongfeng-Tongji Cohort Study

OBJECTIVE

The objective of this study is to examine whether healthy lifestyle could reduce diabetes risk among individuals with different genetic profiles.

DESIGN

A prospective cohort study with a median follow-up of 4.6 years from the Dongfeng-Tongji cohort was performed.

PARTICIPANTS

A total of 19 005 individuals without diabetes at baseline participated in the study.

MAIN VARIABLE MEASURE

A healthy lifestyle was determined based on 6 factors: nonsmoker, nondrinker, healthy diet, body mass index of 18.5 to 23.9 kg/m2, waist circumference less than 85 cm for men and less than 80 cm for women, and higher level of physical activity. Associations of combined lifestyle factors and incident diabetes were estimated using Cox proportional hazard regression. A polygenic risk score of 88 single-nucleotide polymorphisms previously associated with diabetes was constructed to test for association with diabetes risk among 7344 individuals, using logistic regression.

RESULTS

A total of 1555 incident diabetes were ascertained. Per SD increment of simple and weighted genetic risk score was associated with a 1.39- and 1.34-fold higher diabetes risk, respectively. Compared with poor lifestyle, intermediate and ideal lifestyle were reduced to a 23% and 46% risk of incident diabetes, respectively. Association of lifestyle with diabetes risk was independent of genetic risk. Even among individuals with high genetic risk, intermediate and ideal lifestyle were separately associated with a 29% and 49% lower risk of diabetes.

CONCLUSION

Genetic and combined lifestyle factors were independently associated with diabetes risk. A healthy lifestyle could lower diabetes risk across different genetic risk categories, emphasizing the benefit of entire populations adhering to a healthy lifestyle.

Cross-sectional study of the association between skin tags and vascular risk factors in a bariatric clinic-based cohort of Irish adults with morbid obesity

OBJECTIVE

Skin tags are associated with an insulin resistant phenotype but studies in White Europeans with morbid obesity are lacking. We sought to determine whether the presence of cervical or axillary skin tags was associated with increased cardiovascular risk in Irish adults with morbid obesity. We conducted a cross-sectional study of patients attending our Irish regional bariatric centre with a BMI ≥ 40 kg m^-2 (or ≥ 35 kg m^-2 with co-morbidities). We compared anthropometric and metabolic characteristics in those with versus without skin tags.

RESULTS

Of 164 patients, 100 (31 male, 37 with type 2 diabetes, 36 on lipid lowering therapy, 41 on antihypertensive therapy) participated. Mean age was 53.7 ± 11.3 (range 31.1-80) years. Cervical or axillary tags were present in 85 patients. Those with tags had higher systolic blood pressure 138.0 ± 16.0 versus 125.1 ± 8.3 mmHg, p = 0.003) and HbA1c (46.5 ± 13.2 versus 36.8 ± 3.5 mmol/mol, p = 0.017). Tags were present in 94.6% of patients with diabetes, compared to 79.4% of those without diabetes (p = 0.039). Antihypertensive therapy was used by 45.8% of patients with skin tags compared to 13.3% without tags (p = 0.018). In bariatric clinic attenders skin tags were associated with higher SBP and HbA1c and a higher prevalence of diabetes and hypertension, consistent with increased vascular risk, but lipid profiles were similar.

Excess body weight, cigarette smoking, and type II diabetes incidence in the national FINRISK studies

PURPOSE

We identify the individual and joint contributions of excess weight and cigarette smoking to national-level type II diabetes (T2D) incidence and to educational and gender disparities therein filling an important gap in T2D epidemiology.

METHODS

Based on the FINRISK surveys conducted in 1997, 2002, and 2007 and linked to the Finnish National Drug Reimbursement Register through 2011, we used a regression-counterfactual approach to estimate the percentage of diagnosed drug-treated incident T2D cases attributable to excess body weight and cigarette smoking. Body mass index (BMI) and waist circumference were evaluated.

RESULTS

T2D incidence was 10.24 in men and 7.04 in women per 1000 person-years. Excess baseline BMI (≥25.0 kg/m²) explained 69% and 63%, and smoking explained 9% and 14% of T2D incidence, in men and women, respectively. Most of the gender difference was explained by the risk factors. Approximately 90% in men and 98% in women of the higher T2D incidence among those in the lower versus upper third of the educational distribution was explained by excess BMI. The results were similar for waist circumference and lifetime maximum BMI.

CONCLUSIONS

Excess body weight is the main risk factor contributing to national-level T2D incidence and disparities by educational attainment and gender in a high-income population.

Cost-Effectiveness of Three Doses of a Behavioral Intervention to Prevent or Delay Type 2 Diabetes in Rural Areas

BACKGROUND

Rural Americans have higher prevalence of obesity and type 2 diabetes (T2D) than urban populations and more limited access to behavioral programs to promote healthy lifestyle habits. Descriptive evidence from the Rural Lifestyle Intervention Treatment Effectiveness trial delivered through local cooperative extension service offices in rural areas previously identified that behavioral modification with both nutrition education and coaching resulted in a lower program delivery cost per kilogram of weight loss maintained at 2-years compared with an education-only comparator intervention.

OBJECTIVE

This analysis extended earlier Rural Lifestyle Intervention Treatment Effectiveness trial research regarding weight loss outcomes to assess whether nutrition education with behavioral coaching delivered through cooperative extension service offices is cost-effective relative to nutrition education only in reducing T2D cases in rural areas.

DESIGN

A cost-utility analysis was conducted.

PARTICIPANTS/SETTING

Trial participants (n=317) from June 2008 through June 2014 were adults residing in rural Florida counties with a baseline body mass index between 30 and 45, but otherwise identified as healthy.

INTERVENTION

Trial participants were randomly assigned to low, moderate, or high doses of behavioral coaching with nutrition education (ie, 16, 32, or 48 sessions over 24 months) or a comparator intervention that included 16 sessions of nutrition education without coaching. Participant glycated hemoglobin level was measured at baseline and the end of the trial to assess T2D status.

MAIN OUTCOME MEASURES

T2D categories by treatment arm were used to estimate participants' expected annual health care expenditures and expected health-related utility measured as quality adjusted life years (ie, QALYs) over a 5-year time horizon. Discounted incremental costs and QALYs were used to calculate incremental cost-effectiveness ratios for each behavioral coaching intervention dose relative to the education-only comparator.

STATISTICAL ANALYSES PERFORMED

Using a third-party payer perspective, Markov transition matrices were used to model participant transitions between T2D states. Replications of the individual participant behavior were conducted using Monte Carlo simulation.

RESULTS

All three doses of the behavioral coaching intervention had lower expected total costs and higher estimated QALYs than the education-only comparator. The moderate dose behavioral coaching intervention was associated with higher estimated QALYs but was costlier than the low dose; the moderate dose was favored over the low dose with willingness to pay thresholds over $107,895/QALY. The low dose behavioral coaching intervention was otherwise favored.

CONCLUSIONS

Because most rural Americans live in counties with cooperative extension service offices, nutrition education with behavioral coaching programs similar to those delivered through this trial may be effective and efficient in preventing or delaying T2D-associated consequences of obesity for rural adults.

Quantifying Importance of Major Risk Factors for Coronary Heart Disease

Supplemental Digital Content is available in the text.

Background:

To optimize preventive strategies for coronary heart disease (CHD), it is essential to understand and appropriately quantify the contribution of its key risk factors. Our objective was to compare the associations of key modifiable CHD risk factors—specifically lipids, systolic blood pressure (SBP), diabetes mellitus, and smoking—with incident CHD events based on their prognostic performance, attributable risk fractions, and treatment benefits, overall and by age.

Methods:

Pooled participant-level data from 4 observational cohort studies sponsored by the National Heart, Lung, and Blood Institute were used to create a cohort of 22 626 individuals aged 45 to 84 years who were initially free of cardiovascular disease. Individuals were followed for 10 years from baseline evaluation for incident CHD. Proportional hazards regression was used to estimate metrics of prognostic model performance (likelihood ratio, C index, net reclassification, discrimination slope), hazard ratios, and population attributable fractions for SBP, non–high-density lipoprotein cholesterol (non–HDL-C), diabetes mellitus, and smoking. Expected absolute risk reductions for antihypertensive and lipid-lowering treatment were assessed.

Results:

Age, sex, and race capture 63% to 80% of the prognostic performance of cardiovascular risk models. In contrast, adding either SBP, non–HDL-C, diabetes mellitus, or smoking to a model with other risk factors increases the C index by only 0.004 to 0.013. However, primordial prevention could have a substantial effect as demonstrated by population attributable fractions of 28% for SBP≥130 mm Hg and 17% for non–HDL-C≥130 mg/dL. Similarly, lowering the SBP of all individuals to <130 mm Hg or lowering low-density lipoprotein cholesterol by 30% would be expected to lower a baseline 10-year CHD risk of 10.7% to 7.0 and 8.0, respectively (absolute risk reductions: 3.7% and 2.7%, respectively). Prognostic performance decreases with age (C indices for age groups 45–54, 55–64, 65–74, 75–84 are 0.75, 0.72, 0.66, and 0.62, respectively), whereas absolute risk reductions increase (SBP: 1.1%, 2.3%, 5.4%, 10.3%, respectively; non–HDL-C: 1.1%, 2.0%, 3.7%, 5.9%, respectively).

Conclusions:

Although individual modifiable CHD risk factors contribute only modestly to prognostic performance, our models indicate that eliminating or controlling these individual factors would lead to substantial reductions in total population CHD events. Metrics used to judge importance of risk factors should be tailored to the research objectives.

Strong adherence to dietary and lifestyle recommendations is associated with decreased type 2 diabetes risk in the AusDiab cohort study

We aimed to determine whether adherence to the Australian dietary guidelines and an index of healthy behavior was associated with a lower risk of type 2 diabetes (T2D) and to provide estimates of the proportion of preventable cases. Participants of the AusDiab cohort study were followed for 12 years (n = 6242), starting from May 1999, during which T2D cases were identified. The associations between T2D risk and a score of adherence to the dietary guidelines, its components, and a score of adherence to an index of healthy behaviors, (which included smoking, recreational physical activity, waist circumference and adherence to the dietary guidelines), were estimated using Cox proportional hazards ratios (HR) and 95% confidence intervals. The proportion of preventable cases was estimated using the population attributable fraction (PAF). Strong adherence to the dietary guidelines was not associated with T2D risk (HR = 0.64 [95% CI 0.39-1.06]), unless moderate alcohol consumption was considered as beneficial instead of no alcohol consumption (HR = 0.59 [0.36-0.96]). However, strong adherence to the guidelines regarding fruit and dairy intake were both associated with decreased risk of T2D (HR = 0.68 [0.51-0.91]; 0.56 [0.38-0.84], respectively) and could have prevented 23-37% of cases (PAF = 23.3% [7.3-38.2]; 37.1% [14.6-56.0], respectively). Strong adherence to the index of healthy behaviors was associated with decreased risk of T2D (HR = 0.30 [0.17-0.51]) and estimated to prevent almost 60% of T2D (PAF = 59.4% [34.3-76.6]). More than half of T2D cases could be preventable in Australia through modifying health behavior. These results could serve as a basis for prevention programs based on lifestyle modification.

Etiology and Pathogenesis of Latent Autoimmune Diabetes in Adults (LADA) Compared to Type 2 Diabetes

As the heterogeneity of diabetes is becoming increasingly clear, opportunities arise for more accurate assessment of factors influencing disease onset, which may lead to more efficient primary prevention. LADA - latent autoimmune diabetes in adults - is a common, hybrid form of diabetes with features of both type 1 and type 2 diabetes. This review aims to summarize current knowledge on the pathophysiological and etiological overlap and differences between LADA and type 2 diabetes, discuss similarities between LADA and type 1 diabetes and point at future research needs. Studies conducted to date show a clear genetic overlap between LADA and type 1 diabetes with a high risk conferred by variants in the human leukocyte antigen (HLA) region. In contrast, data from the limited number of studies on lifestyle factors available indicate that LADA may share several environmental risk factors with type 2 diabetes including overweight, physical inactivity, alcohol consumption (protective) and smoking. These factors are known to influence insulin sensitivity, suggesting that insulin resistance, in addition to insulin deficiency due to autoimmune destruction of the beta cells, may play a key role in the pathogenesis of LADA. Moreover, this implies that onset of LADA, similar to type 2 diabetes, to some extent could be prevented or postponed by lifestyle modification such as weight reduction and increased physical activity. The preventive potential of LADA is an important topic to elucidate in future studies, preferably intervention studies.

Population attributable fractions of the main type 2 diabetes mellitus risk factors in women: Findings from the French E3N cohort

BACKGROUND

Although many type 2 diabetes mellitus (T2DM) risk factors have been identified, little is known regarding their contributions to the diabetes burden at the population level.

METHODS

The study included 72 655 French women from the Etude Epidemiologique de Femmes de la Mutuelle Générale de l'Education Nationale (E3N) prospective cohort followed between 1993 and 2011. Cox multivariable models including the main T2DM risk factors (metabolic, dietary, clinical, socioeconomic and hormonal) and a healthy lifestyle index combining five characteristics (smoking, body mass index [BMI], alcohol consumption, fruit and vegetable consumption, and physical activity) were used to estimate hazard ratios and population attributable fractions (PAFs) for T2DM.

RESULTS

In multivariate models, factors with the strongest effect on T2DM risk were, in decreasing order, BMI ≥ 30 kg/m² (PAF = 43%; 95% confidence interval [CI] 37-47), high adherence to a Western dietary pattern (PAF = 30%; 95% CI 20-40), hypertension (PAF = 26%; 95% CI 20-32), an acidogenic diet (PAF = 24%; 95% CI 16-32), a family history of diabetes (PAF = 20%; 95% CI 17-22), and, with a negative correlation, moderate alcohol consumption (PAF-19%; 95% CI -34, -4). The PAF for an unhealthy lifestyle was 57% (95% CI 50-63).

CONCLUSIONS

We have been able to sort out and quantify the effect of various dietary and biological T2DM risk factors simultaneously in a single population, and to highlight the importance of a healthy lifestyle for primary prevention: more than half the T2DM cases could have been prevented through a healthier lifestyle.

The future burden of lung cancer attributable to current modifiable behaviours: a pooled study of seven Australian cohorts

Background

Knowledge of preventable disease and differences in disease burden can inform public health action to improve health and health equity. We quantified the future lung cancer burden preventable by behavioural modifications across Australia.

Methods

We pooled seven Australian cohort studies (n = 367 058) and linked them to national registries to identify lung cancers and deaths. We estimated population attributable fractions and their 95% confidence intervals (CIs) for modifiable risk factors, using risk estimates from the cohort data and risk factor exposure distribution from contemporary national health surveys.

Results

During the first 10-year follow-up, there were 2025 incident lung cancers and 20 349 deaths. Stopping current smoking could prevent 53.7% (95% CI, 50.0-57.2%) of lung cancers over 40 years and 18.3% (11.0-25.1%) in 10 years. The smoking-attributable burden is highest in males, those who smoke <20 cigarettes per day, are <75 years of age, unmarried, of lower educational attainment, live in remote areas or are healthy weight. Increasing physical activity and fruit consumption, if causal, could prevent 15.6% (6.9-23.4%) and 7.5% (1.3-13.3%) of the lung cancer burden, respectively. Jointly, the three behaviour modifications could prevent up to 63.0% (58.0-67.5%) of lung cancers in 40 years, and 31.2% (20.9-40.1%) or 43 300 cancers in 10 years. The preventable burden is highest among those with multiple risk factors.

Conclusions

Smoking remains responsible for the highest burden of lung cancer in Australia. The uneven burden distribution distinguishes subgroups that could benefit the most from activities to control the world's deadliest cancer.

The 2016 global and national burden of diabetes mellitus attributable to PM2·5 air pollution

BACKGROUND

PM_2·5 air pollution is associated with increased risk of diabetes; however, a knowledge gap exists to further define and quantify the burden of diabetes attributable to PM_2·5 air pollution. Therefore, we aimed to define the relationship between PM_2·5 and diabetes. We also aimed to characterise an integrated exposure response function and to provide a quantitative estimate of the global and national burden of diabetes attributable to PM_2·5.

METHODS

We did a longitudinal cohort study of the association of PM_2·5 with diabetes. We built a cohort of US veterans with no previous history of diabetes from various databases. Participants were followed up for a median of 8·5 years, we and used survival models to examine the association between PM_2·5 and the risk of diabetes. All models were adjusted for sociodemographic and health characteristics. We tested a positive outcome control (ie, risk of all-cause mortality), negative exposure control (ie, ambient air sodium concentrations), and a negative outcome control (ie, risk of lower limb fracture). Data for the models were reported as hazard ratios (HRs) and 95% CIs. Additionally, we reviewed studies of PM_2·5 and the risk of diabetes, and used the estimates to build a non-linear integrated exposure response function to characterise the relationship across all concentrations of PM_2·5 exposure. We included studies into the building of the integrated exposure response function if they scored at least a four on the Newcastle-Ottawa Quality Assessment Scale and were only included if the outcome was type 2 diabetes or all types of diabetes. Finally, we used the Global Burden of Disease study data and methodologies to estimate the attributable burden of disease (ABD) and disability-adjusted life-years (DALYs) of diabetes attributable to PM_2·5 air pollution globally and in 194 countries and territories.

FINDINGS

We examined the relationship of PM_2·5 and the risk of incident diabetes in a longitudinal cohort of 1 729 108 participants followed up for a median of 8·5 years (IQR 8·1-8·8). In adjusted models, a 10 μg/m³ increase in PM_2·5 was associated with increased risk of diabetes (HR 1·15, 95% CI 1·08-1·22). PM_2·5 was associated with increased risk of death as the positive outcome control (HR 1·08, 95% CI 1·03-1·13), but not with lower limb fracture as the negative outcome control (1·00, 0·91-1·09). An IQR increase (0·045 μg/m³) in ambient air sodium concentration as the negative exposure control exhibited no significant association with the risk of diabetes (HR 1·00, 95% CI 0·99-1·00). An integrated exposure response function showed that the risk of diabetes increased substantially above 2·4 μg/m³, and then exhibited a more moderate increase at concentrations above 10 μg/m³. Globally, ambient PM_2·5 contributed to about 3·2 million (95% uncertainty interval [UI] 2·2-3·8) incident cases of diabetes, about 8·2 million (95% UI 5·8-11·0) DALYs caused by diabetes, and 206 105 (95% UI 153 408-259 119) deaths from diabetes attributable to PM_2·5 exposure. The burden varied substantially among geographies and was more heavily skewed towards low-income and lower-to-middle-income countries.

INTERPRETATION

The global toll of diabetes attributable to PM_2·5 air pollution is significant. Reduction in exposure will yield substantial health benefits.

FUNDING

US Department of Veterans Affairs.

The Future Colorectal Cancer Burden Attributable to Modifiable Behaviors: A Pooled Cohort Study

BACKGROUND

Previous estimates of the colorectal cancer (CRC) burden attributed to behaviors have not considered joint effects, competing risk, or population subgroup differences.

METHODS

We pooled data from seven prospective Australian cohort studies (n = 367 058) and linked them to national registries to identify CRCs and deaths. We estimated the strength of the associations between behaviors and CRC risk using a parametric piecewise constant hazards model, adjusting for age, sex, study, and other behaviors. Exposure prevalence was estimated from contemporary National Health Surveys. We calculated population attributable fractions for CRC preventable by changes to current behaviors, accounting for competing risk of death and risk factor interdependence. Statistical tests were two-sided.

RESULTS

During the first 10 years of follow-up, there were 3471 incident CRCs. Overweight or obesity explained 11.1%, ever smoking explained 10.7% (current smoking 3.9%), and drinking more than two compared with two or fewer alcoholic drinks per day explained 5.8% of the CRC burden. Jointly, these factors were responsible for 24.9% (95% confidence interval [CI] = 19.7% to 29.9%) of the burden, higher for men (36.7%) than women (13.2%, P difference < .001). The burden attributed to these factors was also higher for those born in Australia (28.7%) than elsewhere (16.8%, P difference = .047). We observed modification of the smoking-attributable burden by alcohol consumption and educational attainment, and modification of the obesity-attributable burden by age group and birthplace.

CONCLUSIONS

We produced up-to-date estimates of the future CRC burden attributed to modifiable behaviors. We revealed novel differences between men and women, and other high-CRC burden subgroups that could potentially benefit most from programs that support behavioral change and early detection.

Population attributable fractions for Type 2 diabetes: an examination of multiple risk factors including symptoms of depression and anxiety

BACKGROUND

Population attributable fractions (PAFs) are frequently used to quantify the proportion of Type 2 diabetes cases due to single risk factors, an approach which may result in an overestimation of their individual contributions. This study aimed to examine Type 2 diabetes incidence associated with multiple risk factor combinations, including the metabolic syndrome, behavioural factors, and specifically, depression and anxiety.

METHODS

Using data from the population-based HUNT cohort, we examined incident diabetes in 36,161 Norwegian adults from 1995 to 2008. PAFs were calculated using Miettinen's case-based formula, using relative risks estimated from multivariate regression models.

RESULTS

Overall, the studied risk factors accounted for 50.5% of new diabetes cases (78.2% in men and 47.0% in women). Individuals exposed to both behavioural and metabolic factors were at highest risk of diabetes onset (PAF = 22.9%). Baseline anxiety and depression contributed a further 13.6% of new cases to this combination. Men appeared to be particularly vulnerable to the interaction between metabolic, behavioural and psychological risk factors.

CONCLUSION

This study highlights the importance of risk factor clustering in diabetes onset, and is the first that we know of to quantify the excess fraction of incident diabetes associated with psychological risk factor interactions.

Time Trends of Dietary and Lifestyle Factors and Their Potential Impact on Diabetes Burden in China

OBJECTIVE

To examine the secular trends in risk factors, estimate their impact on type 2 diabetes burden from 1991 to 2011, and project trends in the next 20 years.

RESEARCH DESIGN AND METHODS

Risk factor distributions were based on data from the China Health and Nutrition Survey 1991-2011. Diabetes cases attributable to all nonoptimal levels of each risk factor were estimated by applying the comparative risk assessment method.

RESULTS

In 2011, high BMI was the leading individual attributable factor for diabetes cases in China responsible for 43.8 million diabetes cases with a population-attributable fraction of 46.8%. Low whole-grain intake and high refined grain intake were the leading dietary risk factors in China responsible for 37.8 million and 21.8 million diabetes-attributable cases, respectively. The number of attributable diabetes cases associated with low physical activity, high blood pressure, and current smoking was 29.5, 21.6, and 9.8 million, respectively. Although intakes of low-fat dairy products, nuts, fruit, vegetables, and fish and seafood increased moderately over time, the average intake was below optimal levels in 2011 and were responsible for 15.8, 11.3, 9.9, 6.0, 3.6, and 2.6 million diabetes cases, respectively. Meanwhile, intakes of processed meat, red meat, and sugar-sweetened beverage showed increasing trends over time and were responsible for 2.8, 1.8, and 0.5 million diabetes cases, respectively, in 2011.

CONCLUSIONS

A high BMI and low intake of whole grains but high intake of refined grains are the most important individual risk factors related to Chinese diabetes burden; low physical activity and high blood pressure also significantly contributed.

Adherence to a healthy lifestyle and the risk of type 2 diabetes in Chinese adults

Background

Simultaneously adhering to multiple healthy lifestyle factors has been related to up to 90% reduction in type 2 diabetes (T2DM) incidence in White populations; however, little is known about whether such protective effects persist in other non-White populations.

Methods

We examined the associations of six lifestyle factors with T2DM in the China Kadoorie Biobank of 461 211 participants aged 30-79 years without diabetes, cardiovascular diseases or cancer at baseline. We defined low-risk lifestyle factors as non-smoking or having stopped for reasons other than illness; alcohol consumption of <30 g/day; upper quarter of the physical activity level; diet rich in vegetables and fruits, low in red meat and with some degree of replacement of rice with wheat; body mass index (BMI) of 18.5-23.9 kg/m2; and waist-to-hip ratio (WHR) <0.90 (men)/<0.85 (women).

Results

During a median of 7.2 years of follow-up, we identified 8784 incident T2DM. In multivariable-adjusted analyses, two important risk factors for developing T2DM were higher BMI and WHR. Compared with participants without any low-risk factors, the hazard ratio [95% confidence interval (CI)] for those with at least three low-risk factors was 0.20 (0.19, 0.22). Approximately 72.6% (64.2%, 79.3%) of the incident diabetes were attributable to the combination of BMI, WHR, diet and physical activity. The population attributable risk percentage (PAR%) of diabetes appeared to be similar for men and women, and higher among urban, older and obese participants.

Conclusions

Our findings indicate that adherence to a healthy lifestyle may substantially lower the burden of T2DM in the Chinese population.

The Relation of Type 2 Diabetes and Breast Cancer Incidence in Asian, Hispanic and African American Populations-A Review

In addition to rising type 2 diabetes and breast cancer incidence rates worldwide, diabetes may also increase breast cancer risk, and the association may vary by ethnicity. This review summarizes published data evaluating the association between diabetes and breast cancer in women of Asian, Hispanic and African American ancestry while considering a measure of obesity, body mass index (BMI). Published reports were identified through a search of PubMed and previous publications. Of 15 age-adjusted studies, 11 reported on Asian women from various countries, 3 on Hispanics and 1 on African Americans. The studies of Asian women described significant associations in 8 reports, with risk estimates of 1.5 to 8.4, but 3 were case-control studies and 6 did not adjust for BMI. The 3 case-control studies of Hispanic people included BMI, but only 1 detected a weak association between diabetes and breast cancer risk and was limited to postmenopausal women. The only study of African American women was a prospective cohort, and it showed no significant association between diabetes and breast cancer. In contrast to a 10% to 20% higher risk for breast cancer associated with diabetes reported for Caucasian women, there is little evidence for an association in Hispanics and African Americans. Although several studies of Asian women included in our review reported a higher risk for breast cancer with diabetes, methodologic shortcomings, such as lack of adjustment for obesity, use of a general population as controls, case-control design and small sample sizes, raise questions about the validity of the findings.

Impact of weight maintenance and loss on diabetes risk and burden: a population-based study in 33,184 participants

BACKGROUND

Weight loss in individuals at high risk of diabetes is an effective prevention method and a major component of the currently prevailing diabetes prevention strategies. The aim of the present study was to investigate the public health potential for diabetes prevention of weight maintenance or moderate weight loss on a population level in an observational cohort with repeated measurements of weight and diabetes status.

METHODS

Height, weight and diabetes status were objectively measured at baseline and 10 year follow-up in a population-based cohort of 33,184 participants aged 30-60 years between 1990 and 2013 in Västerbotten County, Sweden. The association between risk of incident diabetes and change in BMI or relative weight was modelled using multivariate logistic regression. Population attributable fractions (PAF) were used to assess population impact of shift in weight.

RESULTS

Mean (SD) BMI at baseline was 25.0 (3.6) kg/m². Increase in relative weight between baseline and follow-up was linearly associated with incident diabetes risk, odds ratio (OR) 1.05 (95% confidence interval (CI) 1.04-1.06) per 1% change in weight. Compared to weight maintenance (±1.0 kg/m²), weight gain of > +1.0 kg/m² was associated with an increased risk of incident diabetes, OR 1.52 (95% CI 1.32, 1.74), representing a PAF of 21.9% (95% CI 15.8, 27.6%). For moderate weight loss (-1.0 to -2.0 kg/m²) the OR was 0.72 (95% CI 0.52, 0.99).

CONCLUSIONS

Weight maintenance in adulthood is strongly associated with reduced incident diabetes risk and there is considerable potential for diabetes prevention in promoting this as a whole population strategy.

Milk and dairy products: good or bad for human health? An assessment of the totality of scientific evidence

Background

There is scepticism about health effects of dairy products in the public, which is reflected in an increasing intake of plant-based drinks, for example, from soy, rice, almond, or oat.

Objective

This review aimed to assess the scientific evidence mainly from meta-analyses of observational studies and randomised controlled trials, on dairy intake and risk of obesity, type 2 diabetes, cardiovascular disease, osteoporosis, cancer, and all-cause mortality.

Results

The most recent evidence suggested that intake of milk and dairy products was associated with reduced risk of childhood obesity. In adults, intake of dairy products was shown to improve body composition and facilitate weight loss during energy restriction. In addition, intake of milk and dairy products was associated with a neutral or reduced risk of type 2 diabetes and a reduced risk of cardiovascular disease, particularly stroke. Furthermore, the evidence suggested a beneficial effect of milk and dairy intake on bone mineral density but no association with risk of bone fracture. Among cancers, milk and dairy intake was inversely associated with colorectal cancer, bladder cancer, gastric cancer, and breast cancer, and not associated with risk of pancreatic cancer, ovarian cancer, or lung cancer, while the evidence for prostate cancer risk was inconsistent. Finally, consumption of milk and dairy products was not associated with all-cause mortality. Calcium-fortified plant-based drinks have been included as an alternative to dairy products in the nutrition recommendations in several countries. However, nutritionally, cow's milk and plant-based drinks are completely different foods, and an evidence-based conclusion on the health value of the plant-based drinks requires more studies in humans.

Conclusion

The totality of available scientific evidence supports that intake of milk and dairy products contribute to meet nutrient recommendations, and may protect against the most prevalent chronic diseases, whereas very few adverse effects have been reported.

Diabetes mellitus in Zambia and the Western Cape province of South Africa: Prevalence, risk factors, diagnosis and management

AIMS

To determine the prevalence of and risk factors for diabetes mellitus and examine its diagnosis and management in the study communities.

METHODS

This is a population-based cross-sectional study among adults in 24 communities from Zambia and the Western Cape (WC) province of South Africa. Diabetes is defined as a random blood glucose concentration (RBG)⩾11.1mmol/L, or RBG<11.1mmol/L but with a self-reported prior diabetes diagnosis. For individuals with a prior diagnosis of diabetes, RBG<7.8mmol/L was considered to be an acceptable level of glycaemia.

RESULTS

Among 45,767 Zambian and 12,496 WC participants the age-standardised prevalence of diabetes was 3.5% and 7.2% respectively. The highest risk groups identified were those of older age and those with obesity. Of those identified to have diabetes, 34.5% in Zambia and 12.7% in WC were previously unaware of their diagnosis. Among Zambian participants with diabetes, this proportion was lower among individuals with better education or with higher household socio-economic position. Of all those with previously diagnosed diabetes, 66.0% in Zambia and 59.4% in WC were not on any diabetes treatment, and 34.4% in Zambia and 32.7% in WC had a RBG concentration beyond the recommended level, ⩾7.8mmol/L.

CONCLUSIONS

The diabetes risk factor profile for our study communities is similar to that seen in high-income populations. A high proportion of individuals with diabetes are not on diabetes treatment and of those on treatment a high proportion have high glycaemic concentrations. Such data may assist in healthcare planning to ensure timely diagnosis and management of diabetes.

Muscle grip strength predicts incident type 2 diabetes: Population-based cohort study

OBJECTIVES

To determine the longitudinal relationship of muscle mass and strength with incident type 2 diabetes, and previously unstudied mediating effects of testosterone and inflammation.

METHODS

Community-dwelling male participants (aged ≥35years) of the Men Androgen Inflammation Lifestyle Environment and Stress (MAILES) Study underwent biomedical assessment in 2002-2006 and 2007-2010, including hand grip strength (dynamometer), testosterone and inflammatory markers. Body composition (dual-energy X-ray absorptiometry) was assessed at baseline only. Incident type 2 diabetes was defined as a self-reported doctor diagnosis, diabetes medication use, fasting plasma glucose ≥7.0mmol/L, or glycated haemoglobin ≥6.5% (48mmol/mol) at follow-up, that was not present at baseline.

RESULTS

Of n=1632 men, incident type 2 diabetes occurred in 146 (8.9%). Muscle mass was not associated with incident type 2 diabetes. Grip strength was inversely associated with incident type 2 diabetes [unadjusted odds ratio (OR) per 5kg: 0.87, 95% confidence interval (CI): 0.80-0.95; adjusted OR, 95% CI: 0.87, 0.78-0.97]. Arm muscle quality (grip strength divided by arm lean mass) was similarly associated with incident type 2 diabetes. Testosterone, IL-6 and TNF-α did not significantly mediate the associations. The population attributable fraction of type 2 diabetes from low grip strength was 27% (13-40%), assuming intervention could increase strength by 25%.

CONCLUSIONS

Reduced muscle strength, but not reduced muscle mass, is a risk factor for incident type 2 diabetes in men. This is not mediated by testosterone or inflammation. Intervention could prevent a substantial proportion of disease.

Racial-ethnic disparities in the association between risk factors and diabetes: The Northern Manhattan Study

PURPOSE

To identify risk factors (RF) for diabetes within a multiethnic cohort and to examine whether race-ethnicity modified their effects.

METHODS

Participants in the Northern Manhattan Study without diabetes at baseline were studied from 1993 to 2014 (n=2430). Weibull regression models with interval censoring data were fit to calculate hazard ratios and 95% confidence intervals for incident diabetes. We tested for interactions between RF and race-ethnicity.

RESULTS

During a mean follow-up period of 11years, there were 449 diagnoses of diabetes. Being non-Hispanic black (HR 1.69 95% CI 1.11-2.59) or Hispanic (HR 2.25 95% CI 1.48-3.40) versus non-Hispanic white, and body mass index (BMI; HR 1.34 per SD 95% CI 1.21-1.49) were associated with greater risk of diabetes; high-density lipoprotein cholesterol (HR 0.75 95% CI 0.66-0.86) was protective. There were interactions by race-ethnicity. In stratified models, the effects of BMI, current smoking, and C-reactive protein (CRP) on risk of diabetes differed by race-ethnicity (p for interaction <0.05). The effects were greater among non-Hispanic whites than non-Hispanic blacks and Hispanics.

CONCLUSIONS

Although Hispanics and non-Hispanic blacks had a greater risk of diabetes than whites, there were variations by race-ethnicity in the association of BMI, smoking, and CRP with risk of diabetes. Unique approaches should be considered to reduce diabetes as traditional RF may not be as influential in minority populations.

Acute effect of red meat and dairy on glucose and insulin: a randomized crossover study

BACKGROUND

In contrast with some epidemiologic evidence, our previous research showed that a 4-wk diet that was high in low-fat dairy reduced insulin sensitivity compared with the effect of a diet that was high in red meat.

OBJECTIVE

We investigated whether a dairy meal would produce a greater insulin response than a carbohydrate-matched red meat meal would, which might account for the change in insulin sensitivity.

DESIGN

One meal contained lean red meat, bread, and orange juice, and the other meal contained skim milk, low-fat yogurt, cheese, and bread. Meals were isoenergetic, equal in macronutrient profile, and consumed 1 wk apart. Glucose, insulin, and triglycerides were measured before and 30, 60, 90, 120, 150, and 180 min after meal consumption. Differences between meals were tested with the use of a repeated-measures ANOVA and paired sample t tests.

RESULTS

Nineteen men and 24 women [mean ± SD age: 50.8 ± 16.0 y; body mass index (in kg/m(2)): 30.0 ± 3.5] completed the study. Twenty-two participants had normal glucose tolerance, and 21 participants had impaired fasting glucose or impaired glucose tolerance. The red meat meal resulted in a higher glucose response at 30 min after consumption (P < 0.001); however, the glucose total AUC was not different between meals (P = NS). The mean ± SEM incremental AUC (iAUC) for glucose was significantly higher after the dairy meal than after the red meat meal (2.23 ± 0.49 compared with 0.88 ± 0.57 mmol/L · 3 h, respectively; P = 0.004). The insulin total AUC and iAUC were not different between meals (iAUC: 159.65 ± 20.0 mU/L · 3 h for red meat compared with 167.49 ± 24.1 mU/L · 3 h for dairy; P = NS).

CONCLUSIONS

Lean red meat and low-fat dairy produced a similar glycemic response. The higher glucose response 30 min after consumption of the red meat meal was likely attributable to differences in the glycemic load between orange juice and milk and yogurt. An insulinotropic effect of dairy was not observed. This trial was registered at www.anzctr.org.au as ACTRN12615000164594.

Effects of exercise and metformin on the prevention of glucose intolerance: a comparative study

We aimed to evaluate the effects of aerobic exercise training (4 days) and metformin exposure on acute glucose intolerance after dexamethasone treatment in rats. Forty-two adult male Wistar rats (8 weeks old) were divided randomly into four groups: sedentary control (SCT), sedentary dexamethasone-treated (SDX), training dexamethasone-treated (DPE), and dexamethasone and metformin treated group (DMT). Glucose tolerance tests and in situ liver perfusion were undertaken on fasting rats to obtain glucose profiles. The DPE group displayed a significant decrease in glucose values compared with the SDX group. Average glucose levels in the DPE group did not differ from those of the DMT group, so we suggest that exercise training corrects dexamethasone-induced glucose intolerance and improves glucose profiles in a similar manner to that observed with metformin. These data suggest that exercise may prevent the development of glucose intolerance induced by dexamethasone in rats to a similar magnitude to that observed after metformin treatment.

Maternal obesity during pregnancy and cardiovascular development and disease in the offspring

Maternal obesity during pregnancy is an important public health problem in Western countries. Currently, obesity prevalence rates in pregnant women are estimated to be as high as 30 %. In addition, approximately 40 % of women gain an excessive amount of weight during pregnancy in Western countries. An accumulating body of evidence suggests a long-term impact of maternal obesity and excessive weight gain during pregnancy on adiposity, cardiovascular and metabolic related health outcomes in the offspring in fetal life, childhood and adulthood. In this review, we discuss results from recent studies, potential underlying mechanisms and challenges for future epidemiological studies.

Higher serum 25-hydroxyvitamin D concentrations are related to a reduced risk of depression

Vitamin D has been suggested to protect against depression, but epidemiological evidence is scarce. The present study investigated the relationship of serum 25-hydroxyvitamin D (25(OH)D) with the prevalence of depressive and anxiety disorders. The study population consisted of a representative sample of Finnish men and women aged 30-79 years from the Health 2000 Survey. The sample included 5371 individuals, of which 354 were diagnosed with depressive disorder and 222 with anxiety disorder. Serum 25(OH)D concentration was determined from frozen samples. In a cross-sectional study, a total of four indicators of depression and one indicator of anxiety were used as dependent variables. Serum 25(OH)D was the risk factor of interest, and logistic models used further included sociodemographic and lifestyle variables as well as indicators of metabolic health as confounding and/or effect-modifying factors. The population attributable fraction (PAF) was estimated. Individuals with higher serum 25(OH)D concentrations showed a reduced risk of depression. The relative odds between the highest and lowest quartiles was 0.65 (95% CI 0.46, 0.93; P for trend = 0.006) after adjustment for sociodemographic, lifestyle and metabolic factors. Higher serum 25(OH)D concentrations were associated with a lower prevalence of depressive disorder especially among men, younger, divorced and those who had an unhealthy lifestyle or suffered from the metabolic syndrome. The PAF was estimated to be 19% for depression when serum 25(OH)D concentration was at least 50 nmol/l. These results support the hypothesis that higher serum 25(OH)D concentrations protect against depression even after adjustment for a large number of sociodemographic, lifestyle and metabolic factors. Large-scale prospective studies are needed to confirm this finding.

Effects of an eight-week supervised, structured lifestyle modification programme on anthropometric, metabolic and cardiovascular risk factors in severely obese adults

BACKGROUND

Lifestyle modification is fundamental to obesity treatment, but few studies have described the effects of structured lifestyle programmes specifically in bariatric patients. We sought to describe changes in anthropometric and metabolic characteristics in a cohort of bariatric patients after participation in a nurse-led, structured lifestyle programme.

METHODS

We conducted a retrospective, observational cohort study of adults with a body mass index (BMI) ≥ 40 kgm(-2) (or ≥ 35 kgm(-2) with significant co-morbidity) who were attending a regional bariatric service and who completed a single centre, 8-week, nurse-led multidisciplinary lifestyle modification programme. Weight, height, waist circumference, blood pressure, HbA1c, fasting glucose and lipid profiles as well as functional capacity (Incremental Shuttle Walk Test) and questionnaire-based anxiety and depression scores before and after the programme were compared in per-protocol analyses.

RESULTS

Of 183 bariatric patients enrolled, 150 (81.9%) completed the programme. Mean age of completers was 47.9 ± 1.2 years. 34.7% were male. There were statistically significant reductions in weight (129.6 ± 25.9 v 126.9 ± 26.1 kg, p < 0.001), BMI (46.3 ± 8.3 v 44.9 ± 9.0 kgm(-2), p < 0.001), waist circumference (133.0 ± 17.1 v 129.3 ± 17.5 cm in women and 143.8 ± 19.0 v 135.1 ± 17.9 cm in men, both p < 0.001) as well as anxiety and depression scores, total- and LDL-cholesterol and triglyceride levels, with an increase in functional capacity (5.9 ± 1.7 v 6.8 ± 2.1 metabolic equivalents of thermogenesis (METS), p < 0.001) in completers at the end of the programme compared to the start. Blood pressure improved, with reductions in systolic and diastolic blood pressure from 135 ± 16.2 to 131.6 ± 17.1 (p = 0.009) and 84.7 ± 10.2 to 81.4 ± 10.9 mmHg (p < 0.001), respectively. The proportion of patients achieving target blood pressure increased from 50.3 to 59.3% (p = 0.04). The proportion of patients with diabetes achieving HbA1c <53 mmol/mol increased from 28.6 to 42.9%, p = 0.02.

CONCLUSIONS

Bariatric patients completing an 8 week, nurse-led structured lifestyle programme had improved adiposity, fitness, lipid profiles, psychosocial health, blood pressure and glycaemia. Further assessment of this programme in a pragmatic randomised controlled trial seems warranted.

Physical activity and the risk of type 2 diabetes: a systematic review and dose-response meta-analysis

We investigated the association between specific types of physical activity and the risk of type 2 diabetes in a systematic review and meta-analysis of published studies. PubMed, Embase and Ovid databases were searched for prospective studies and randomized trials up to 2nd of March 2015. Summary relative risks (RRs) were calculated using a random effects model. Eighty-one studies were included. The summary RRs for high versus low activity were 0.65 (95 % CI 0.59-0.71, I(2) = 18 %, n = 14) for total physical activity, 0.74 (95 % CI 0.70-0.79, I(2) = 84 %, n = 55) for leisure-time activity, 0.61 (95 % CI 0.51-0.74, I(2) = 73 %, n = 8) for vigorous activity, 0.68 (95 % CI 0.52-0.90, I(2) = 93 %, n = 5) for moderate activity, 0.66 (95 % CI 0.47-0.94, I(2) = 47 %, n = 4) for low intensity activity, and 0.85 (95 % CI 0.79-0.91, I(2) = 0 %, n = 7) for walking. Inverse associations were also observed for increasing activity over time, resistance exercise, occupational activity and for cardiorespiratory fitness. Nonlinear relations were observed for leisure-time activity, vigorous activity, walking and resistance exercise (p nonlinearity < 0.0001 for all), with steeper reductions in type 2 diabetes risk at low activity levels than high activity levels. This meta-analysis provides strong evidence for an inverse association between physical activity and risk of type 2 diabetes, which may partly be mediated by reduced adiposity. All subtypes of physical activity appear to be beneficial. Reductions in risk are observed up to 5-7 h of leisure-time, vigorous or low intensity physical activity per week, but further reductions cannot be excluded beyond this range.

Type 2 diabetes mellitus incidence in Chinese: contributions of overweight and obesity

AIMS

To estimate the incidence of Type 2 diabetes mellitus (T2DM) and the number of those with T2DM attributable to overweight and obesity in China.

METHODS

We conducted a prospective cohort study among 15680 participants (46.4%, men) aged 35-74 years. The mean duration of follow-up was 8.0 years. We examined the relationship between overweight, obesity and risk of T2DM by Cox proportional hazards models. Population attributable risk (PAR) of overweight and obesity was also calculated. Moreover, we estimated the number of T2DM events attributed to overweight and obesity using PAR, incidence of T2DM and the population size of China in 2010.

RESULTS

During a mean follow-up of 8.0 years, the age-standardized incidence of T2DM was 9.5 per 1000 person-years in men and 9.2 in women. Overweight accounted for 28.3% (95% confidence interval [CI]: 20.1, 36.2) of incident T2DM among men and 31.3% (95% CI: 25.5, 36.9) among women. The corresponding PAR of obesity was 10.1% (95% CI: 6.0, 14.2) among men and 16.8% (95% CI: 12.0, 21.6) among women. Approximately 3.32 million (95% CI: 2.47, 4.24) incident T2DM were attributable to overweight and obesity in Chinese adults who were 35 to 74 years in 2010.

CONCLUSION

Our results indicate that incident T2DM is mainly attributable to overweight and obesity in China. It is extremely important to advocate healthy lifestyle and prevent excessive weight gain for reducing T2DM burden in China.

The potential use of DNA methylation biomarkers to identify risk and progression of type 2 diabetes

Type 2 diabetes mellitus (T2D) is a slowly progressive disease that can be postponed or even avoided through lifestyle changes. Recent data demonstrate highly significant correlations between DNA methylation and the most important risk factors of T2D, including age and body mass index, in blood and human tissues relevant to insulin resistance and T2D. Also, T2D patients and individuals with increased risk of the disease display differential DNA methylation profiles and plasticity compared to controls. Accordingly, the novel clues to DNA methylation fingerprints in blood and tissues with deteriorated metabolic capacity indicate that blood-borne epigenetic biomarkers of T2D progression might become a reality. This Review will address the most recent associations between DNA methylation and diabetes-related traits in human tissues and blood. The overall focus is on the potential of future epigenome-wide studies, carried out across tissues and populations with correlations to pre-diabetes and T2D risk factors, to build up a library of epigenetic markers of risk and early progression of T2D. These markers may, tentatively in combination with other predictors of T2D development, increase the possibility of individual-based lifestyle prevention of T2D and associated metabolic diseases.

Dairy consumption and insulin sensitivity: a systematic review of short- and long-term intervention studies

AIM

Evidence from epidemiological studies suggests that higher consumption of dairy products may be inversely associated with risk of type 2 diabetes and other components of the metabolic syndrome, although the evidence is mixed. Intervention studies that increase dairy intake often involve lifestyle changes, including weight loss, which alone will improve insulin sensitivity. The aim of this review was to examine weight stable intervention studies that assess the effect of an increased intake of dairy products or dairy derived supplements on glucose metabolism and insulin sensitivity.

DATA SYNTHESIS

An electronic search was conducted using MEDLINE, EMBASE, the Cochrane Database and Web of Science for randomised controlled trials altering only dairy intake in humans with no other lifestyle or dietary change, particularly no weight change, and with measurement of glucose or insulin. Healthy participants and those with features of the metabolic syndrome were included. Chronic whey protein supplementation was also included. Ten studies were included in this systematic review.

CONCLUSIONS

In adults, four of the dairy interventions showed a positive effect on insulin sensitivity as assessed by Homeostasis Model Assessment (HOMA); one was negative and five had no effect. As the number of weight stable intervention studies is very limited and participant numbers small, these findings need to be confirmed by larger trials in order to conclusively determine any relationship between dairy intake and insulin sensitivity.

Estimating population attributable fractions to quantify the health burden of obesity

PURPOSE

Obesity is a highly prevalent condition in the United States and elsewhere and is associated with increased mortality and morbidity. Here, we discuss some issues involved in quantifying the health burden of obesity using population attributable fraction (PAF) estimates and provide examples.

METHODS

We searched PubMed for articles reporting attributable fraction estimates for obesity. We reviewed eligible articles to identify methodological concerns and tabulated illustrative examples of PAF estimates for obesity relative to cancer, diabetes, cardiovascular disease, and all-cause mortality.

RESULTS

There is considerable variability among studies regarding the methods used for PAF calculation and the selection of appropriate counterfactuals. The reported estimates ranged from 5% to 15% for all-cause mortality, -0.2% to 8% for all-cancer incidence, 7% to 44% for cardiovascular disease incidence, and 3% to 83% for diabetes incidence.

CONCLUSIONS

To evaluate a given estimate, it is important to consider whether the exposure and outcome were defined similarly for the PAF and for the relative risks, whether the relative risks were suitable for the population at hand, and whether PAF was calculated using correct methods. Strong causal assumptions are not necessarily warranted. In general, PAFs for obesity may be best considered as indicators of association.

Population attributable fraction of type 2 diabetes due to physical inactivity in adults: a systematic review

Background

Physical inactivity is a global pandemic. The population attributable fraction (PAF) of type 2 diabetes mellitus (T2DM) associated with physical inactivity ranges from 3% to 40%. The purpose of this systematic review was to determine the best estimate of PAF for T2DM attributable to physical inactivity and absence of sport participation or exercise for men and women.

Methods

We conducted a systematic review that included a comprehensive search of MEDLINE, EMBASE, SportDiscus, and CINAHL (1946 to April 30 2013) limited by the terms adults and English. Two reviewers screened studies, extracted PAF related data and assessed the quality of the selected studies. We reconstructed 95% CIs for studies missing these data using a substitution method.

Results

Of the eight studies reporting PAF in T2DM, two studies included prospective cohort studies (3 total) and six were reviews. There were distinct variations in quality of defining and measuring physical inactivity, T2DM and adjusting for confounders. In the US, PAFs for absence of playing sport ranged from 13% (95% CI: 3, 22) in men and 29% (95% CI: 17, 41) in women. In Finland, PAFs for absence of exercise ranged from 3% (95% CI: -11, 16) in men to 7% (95% CI: -9, 20) in women.

Conclusions

The PAF of physical inactivity due to T2DM is substantial. Physical inactivity is a modifiable risk factor for T2DM. The contribution of physical inactivity to T2DM differs by sex; PAF also differs if physical inactivity is defined as the absence of ‘sport’ or absence of ‘exercise’.

Associations between diet-related diseases and impaired physiological mechanisms: a holistic approach based on meta-analyses to identify targets for preventive nutrition

In nutrition research, analyzing the relationship between a diet-related chronic disease and impaired metabolism is a common reductionist approach. Meta-analyses have enabled quantification of these relationships. There is, however, a need for more holistic approaches to determine the sequence of connections between diseases and associated physiological mechanisms. The objective of this exhaustive review was to collect scientific evidence – with priority given to quantitative reviews – published between 1950 and 2011 to assess the relationships between major diet-related chronic diseases and deregulated mechanisms. The results revealed that diabetes and obesity are the key diseases that lead to all other diet-related chronic diseases, while cancer, cardiovascular disease, skeletal disease, and sarcopenia are endpoint diseases. Liver disease, kidney disease, digestive disease, and mental illness are consequences as well as causes of other diet-related chronic diseases. All diseases have multifactorial causes, and most result from decreased antioxidant status, acid-base imbalance, increased inflammatory status, impaired carbohydrate/lipid/one-carbon metabolism, impaired functioning of neurons and DNA transcription, hypertension, and/or modified digestive microflora. Nutritional strategies that focus on the prevention of obesity and diabetes should be prioritized in order to reduce the prevalence of other major chronic diseases.