Assessing risk for development of diabetes in young adults

Beneficial Impact of Semicarbazide-Sensitive Amine Oxidase Inhibition on the Potential Cytotoxicity of Creatine Supplementation in Type 2 Diabetes Mellitus

Creatine supplementation of the population with type 2 diabetes mellitus (T2DM) combined with an exercise program is known to be a possible therapy adjuvant with hypoglycemic effects. However, excessive administration of creatine leads to the production of methylamine which is deaminated by the enzyme semicarbazide-sensitive amine oxidase (SSAO) and as a result, cytotoxic compounds are produced. SSAO activity and reaction products are increased in the serum of T2DM patients. Creatine supplementation by diabetics will further augment the activity of SSAO. The current review aims to find a feasible way to ameliorate T2DM for patients who exercise and desire to consume creatine. Several natural agents present in food which are involved in the regulation of SSAO activity directly or indirectly are reviewed. Particularly, zinc-α2-glycoprotein (ZAG), zinc (Zn), copper (Cu), histamine/histidine, caffeine, iron (Fe), and vitamin D are discussed. Inhibiting SSAO activity by natural agents might reduce the potential adverse effects of creatine metabolism in population of T2DM.

Evaluating the utility of self-reported questionnaire data to screen for dysglycemia in young adults: Findings from the US National Health and Nutrition Examination Survey

Dysglycemia, including prediabetes and type 2 diabetes, is dangerous and widespread. Yet, the condition is transiently reversible and sequelae preventable, prompting the use of prediction algorithms to quickly assess dysglycemia status through self-reported data. However, as current algorithms have largely been developed in older populations, their application to younger adults is uncertain considering associations between risk factors and dysglycemia vary by age. We sought to identify sex-specific predictors of current dysglycemia among young adults and evaluate their ability to screen for prediabetes and undiagnosed diabetes. We analyzed 2005-2014 data from the National Health and Nutrition Examination Survey for 3251 participants aged 20-39, who completed an oral glucose tolerance test (OGTT), had not been diagnosed with diabetes, and, for females, were not pregnant. Sex-specific stepwise logistic models were fit with predictors identified from univariate analyses. Risk scores were developed using adjusted odds ratios and model performance was assessed using area under the curve (AUC) measures. The OGTT identified 906 (27.9%) and 78 (2.4%) participants with prediabetes or undiagnosed diabetes, respectively. Predictors of dysglycemia status for males were BMI, age, race, and first-degree family history of diabetes, and, in addition to those, education, delivered baby weight, waist circumference, and vigorous physical activity for females. Our male- and female-specific models demonstrated improved validity to assess dysglycemia presence among young adults relative to the widely-used American Diabetes Association test (AUC = 0.69 vs. 0.61; 0.92 vs. 0.71, respectively). Thus, age-specific scoring algorithms employing questionnaire data show promise and are effective in identifying dysglycemia among young adults.

Building Toward a Population-Based Approach to Diabetes Screening and Prevention for US Adults

PURPOSE OF REVIEW

Evidence-based treatments for prediabetes can prevent and delay the development of type 2 diabetes in adults. In this review, we propose a framework for population-based diabetes prevention that links screening and prevention activities across key stakeholders. We also discuss gaps in current practice, while highlighting opportunities to improve diabetes screening and prevention efforts population-wide.

RECENT FINDINGS

Awareness of diabetes risk is low, and many adults with prediabetes are not identified through existing screening efforts. Accumulating evidence and policies support expansion of the Diabetes Prevention Program (DPP) into clinical and community settings. However, the infrastructure to facilitate referrals and promote data exchange among patients, clinical settings, and community-based DPP programs is lacking. Development of evidence-driven, scalable processes for assessing diabetes risk, screening eligible adults, and delivering preventive treatments are needed to effectively improve the glycemic health of the US adult population.

Undiagnosed Hyperglycaemia and Hypertension as Indicators of the Various Risk Factors of Future Cardiovascular Disease Among Population of Serbian Students

BACKGROUND

A number of risk behaviours, such as smoking, overweight, excessive alcohol intake, insufficient physical activity, excessive and frequent intake of salt, reduced fruit and vegetable intake, increased fat intake, which constitute living habits of an individual can influence the occurrence of hypertension and hyperglycaemia. The changing of these lifestyles can reduce the risk of developing prehypertension and prediabetes.

METHODS

The survey was conducted at student's campuses. The respondents were subjected to the height, weight, blood glucose and blood pressure. Respondents filled in previously created questionnaire that was approved by the Ethics Committee for Biomedical Research Faculty of Pharmacy, University of Belgrade.

RESULTS

The percentage of respondents with a glucose value above the reference value was 14.6% (n=19), 2.4% (n=3) had values greater than 7 mmol/L without being diagnosed with diabetes, and accordingly, 2.4% (n=3) had elevated HbA1c values (above 42 mmol/mol or 6.0%). The percentage of respondents with elevated systolic and diastolic blood pressure was 14.9% and 7.4% respectively. Regarding calculated risk scores, they showed parallel increase with increas-ing of BMI (HPS), systolic and diastolic pressure (OHS), and glucose concentration (OPS).

CONCLUSIONS

When analysing all the factors that could cause the later development of diabetes, which is associated with hypertension as well, it is observed that the student population is very much exposed to those factors. The results of this study cannot be representative for the general population of students, but they can provide recommendations for further research.

Utility of existing diabetes risk prediction tools for young black and white adults: Evidence from the Bogalusa Heart Study

AIMS

To evaluate several adult diabetes risk calculation tools for predicting the development of incident diabetes and pre-diabetes in a bi-racial, young adult population.

METHODS

Surveys beginning in young adulthood (baseline age ≥18) and continuing across multiple decades for 2122 participants of the Bogalusa Heart Study were used to test the associations of five well-known adult diabetes risk scores with incident diabetes and pre-diabetes using separate Cox models for each risk score. Racial differences were tested within each model. Predictive utility and discrimination were determined for each risk score using the Net Reclassification Index (NRI) and Harrell's c-statistic.

RESULTS

All risk scores were strongly associated (p<.0001) with incident diabetes and pre-diabetes. The Wilson model indicated greater risk of diabetes for blacks versus whites with equivalent risk scores (HR=1.59; 95% CI 1.11-2.28; p=.01). C-statistics for the diabetes risk models ranged from 0.79 to 0.83. Non-event NRIs indicated high specificity (non-event NRIs: 76%-88%), but poor sensitivity (event NRIs: -23% to -3%).

CONCLUSIONS

Five diabetes risk scores established in middle-aged, racially homogenous adult populations are generally applicable to younger adults with good specificity but poor sensitivity. The addition of race to these models did not result in greater predictive capabilities. A more sensitive risk score to predict diabetes in younger adults is needed.

Duration and Degree of Weight Gain and Incident Diabetes in Younger Versus Middle-Aged Black and White Adults: ARIC, CARDIA, and the Framingham Heart Study

OBJECTIVE

To determine whether duration and degree of weight gain are differentially associated with diabetes risk in younger versus middle-aged black and white adults.

RESEARCH DESIGN AND METHODS

We combined data from three cohort studies: Atherosclerosis Risk in Communities (ARIC), Coronary Artery Risk Development in Young Adults (CARDIA), and the Framingham Heart Study. A total of 17,404 participants (56% women; 21% black) were stratified by baseline age (younger: ≥30 and <45 years; middle-aged: ≥45 and <60 years) and examined for incident diabetes (median follow-up 9 years). Duration and degree of gain in BMI were calculated as "BMI-years" above one's baseline BMI.

RESULTS

Diabetes incidence per 1,000 person-years in the younger and middle-aged groups was 7.2 (95% CI 5.7, 8.7) and 24.4 (22.0, 26.8) in blacks, respectively, and 3.4 (2.8, 4.0) and 10.5 (9.9, 11.2) in whites, respectively. After adjusting for sex, baseline BMI and other cardiometabolic factors, and age and race interaction terms, gains in BMI-years were associated with higher risk of diabetes in the younger compared with middle-aged groups: hazard ratios for 1-unit increase in log BMI-years in younger versus middle-aged blacks were 1.18 (P = 0.02) and 1.02 (P = 0.39), respectively (P for interaction by age-group = 0.047), and in whites were 1.35 (P < 0.001) and 1.11 (P < 0.001), respectively (P for interaction by age-group = 0.008).

CONCLUSIONS

Although middle-aged adults have higher rates of diabetes, younger adults are at greater relative risk of developing diabetes for a given level of duration and degree of weight gain.

Predictive modeling for incident and prevalent diabetes risk evaluation

With half of individuals with diabetes undiagnosed worldwide and a projected 55% increase of the population with diabetes by 2035, the identification of undiagnosed and high-risk individuals is imperative. Multivariable diabetes risk prediction models have gained popularity during the past two decades. These have been shown to predict incident or prevalent diabetes through a simple and affordable risk scoring system accurately. Their development requires cohort or cross-sectional type studies with a variable combination, number and definition of included risk factors, with their performance chiefly measured by discrimination and calibration. Models can be used in clinical and public health settings. However, the impact of their use on outcomes in real-world settings needs to be evaluated before widespread implementation.

External validation of two diabetes risk scores in a young UK South Asian population

AIMS

To externally validate the Leicester Practice Risk Score (LPRS) and the Leicester Risk Assessment score (LRAS) in a young South Asian population.

METHODS

South Asian participants aged 25-39 years inclusive from a population based screening study were included. The risk scores were calculated and compared to the diagnosis of type 2 diabetes mellitus (T2DM) or T2DM and Impaired Glucose Regulation (IGR, including IFG and IGT) using either an oral glucose tolerance test (OGTT) or a HbA1c (≤48mmol/mol/6.5% and ≤42mmol/mol/6.0% respectively). Measures of discrimination and calibration were calculated.

RESULTS

Of the 331 participants 8 (2.4%) had undiagnosed T2DM and 30 (9.1%) had IGR using an OGTT, 11 (3.4%) and 39 (12.1%) were found using HbA1c. Using the LPRS to detect T2DM on an OGTT gives an area under the ROC curve of 0.91 (95% CI 0.86, 0.97), including those with IGR gives an ROC of 0.72 (0.62-0.81), these values are 0.93 (0.88, 0.98) and 0.68 (0.60, 0.77) when using an HbA1c to define outcome. Acceptable levels of calibration were seen. Similar results are found for the LRAS.

CONCLUSIONS

These scores can be used to identify those with undiagnosed T2DM and/or IGR in a young South Asian population. This is the first study to externally validate scores developed for prevalent undiagnosed disease in this age group using both OGTT and HbA1c.

Risk-assessment score for screening diabetes mellitus among Omani adults

PURPOSE

The purpose of this study was to evaluate a self-administered risk-assessment scoring system for identifying Omani adults with type 2 diabetes mellitus (T2DM).

METHODS

An exploratory cross-sectional design was used. Simple random sampling was used to select 93 adults in Muscat. Ethical approval was obtained from the College of Nursing Research and Ethics Committee. The Finnish Diabetes Risk Score (FINDRISC) was used to collect the data in 2009. Informed consent was obtained from the participants. Data were analysed with the Pearson chi-square test.

RESULTS

A total of 9.7% of the adults had very high FINDRISC and 17.2% had slightly elevated risk of developing T2DM within 10 years. The risk assessment (family history, waist circumference, body mass index, physical activity, dietary intake, hypertension and high blood glucose) of T2DM was significant and positively related to the prediction of T2DM among Omani adults.

Recruiting young adults into a weight loss trial: report of protocol development and recruitment results

Obesity has spread to all segments of the U.S. population. Young adults, aged 18-35 years, are rarely represented in clinical weight loss trials. We conducted a qualitative study to identify factors that may facilitate recruitment of young adults into a weight loss intervention trial. Participants were 33 adults aged 18-35 years with BMI ≥25 kg/m(2). Six group discussions were conducted using the nominal group technique. Health, social image, and "self" factors such as emotions, self-esteem, and confidence were reported as reasons to pursue weight loss. Physical activity, dietary intake, social support, medical intervention, and taking control (e.g. being motivated) were perceived as the best weight loss strategies. Incentives, positive outcomes, education, convenience, and social support were endorsed as reasons young adults would consider participating in a weight loss study. Incentives, advertisement, emphasizing benefits, and convenience were endorsed as ways to recruit young adults. These results informed the Cellphone Intervention for You (CITY) marketing and advertising, including message framing and advertising avenues. Implications for recruitment methods are discussed.

Transportability of the updated diabetes prediction model from Atherosclerosis Risk in Communities Study to a Middle Eastern adult population: community-based cohort study

We validated the transportability of the updated diabetes prediction model from Atherosclerosis Risk in Communities (ARIC) Study, to a Middle Eastern population. We investigated 3,721 participants of the Tehran Lipid and Glucose Study (TLGS) aged ≥20 years, free of diabetes at baseline. They underwent a standard 75gr 2-h post-challenge plasma glucose test that was repeated every 3 years using the same protocol. All the models were tested with respect to discrimination and calibration. We confirm the findings of Kahn et al. (Ann Intern Med 150(11):741-751, 2009) in a middle-aged, Middle Eastern population. We obtained the same predictive discrimination for the ARIC model (C statistic: men 0.790 and women 0.829) as for the TLGS' own model (men 0.824 and women 0.847) and validated a good calibration for the updated ARIC diabetes prediction model in the TLGS sample. Among men, optimal cut-point was set to the score of 31 where the maximum value of sensitivity (71.6%) plus specificity (75.3%) was achieved. Among women, the optimal point was set to the score of 38 with sensitivity of 67.1% and specificity of 85.0%. The updated ARIC model predicted the individual diabetes risk with a high level of sensitivity and specificity in the TLGS population, which was comparable with that of original sample. More parsimonious model incorporating age, family history of diabetes, waist circumference, pulse rate, and fasting plasma glucose, which were significantly associated with the risk of incident diabetes in the TLGS population, could be equally effective in predicting diabetes.

Beta-cell age calculator, a translational yardstick to communicate diabetes risk with patients: tehran lipid and glucose study

Aims. To provide a yardstick for physicians/patients to efficiently communicate/measure incident diabetes risk. Methods. We included data on 5,960 (3,438 women) diabetes-free adults, aged ≥20 years at baseline who either developed diabetes during two consecutive examinations or completed the followup. Age, systolic blood pressure, family history of diabetes, waist-to-height ratio (WHtR), triglyceride-to-high-density lipoprotein cholesterol ratio (TG/HDLD-C), and fasting plasma glucose (FPG) were introduced into an accelerated failure time regression model. Results. Annual diabetes incidence rate was 0.85/1000-person (95% CIs 0.77–0.94). Point-score-system incorporated age (1 point for >65 years), family history of diabetes (4 points), systolic blood pressure (−1 to 3 points), WHtR (−4 to 6 points), TG/HDL-C (1 point for ≥1.5), and FPG (0 to 27 points). Harrell's C statistic = 0.830 (95% CIs 0.808–0.852) and Hosmer-Lemeshow χ² = 9.7 (P for lack of fitness = 0.462) indicated good discrimination and calibration. We defined beta-cell age as chronological age of a person with the same predicted risk but all risk factors at the normal levels (i.e., WHtR 0.50, no family history of diabetes, Ln (TG/HDL-C) = 0.531, and FPG = 4.9 (mmol·L⁻¹)). Conclusion. Hereby, we have made it also possible to estimate wide ranges of “beta-cell age” for most chronological ages to assist clinician with risk communication.

A genotype risk score predicts type 2 diabetes from young adulthood: the CARDIA study

AIMS/HYPOTHESIS

Genotype does not change over the life course and may thus facilitate earlier identification of individuals at high risk for type 2 diabetes. We hypothesised that a genotype score predicts incident type 2 diabetes from young adulthood and improves diabetes prediction models based on clinical risk factors alone.

METHODS

The Coronary Artery Risk Development in Young Adults (CARDIA) study followed young adults (aged 18-30 years, mean age 25) serially into middle adulthood. We used Cox regression to build nested prediction models for incident type 2 diabetes based on clinical risk factors assessed in young adulthood (age, sex, race, parental history of diabetes, BMI, mean arterial pressure, fasting glucose, HDL-cholesterol and triacylglyercol), without and with a 38-variant genotype score. Models were compared with C statistics and continuous net reclassification improvement indices (NRI).

RESULTS

Of 2,439 participants, 830 (34%) were black and 249 (10%) had a BMI ≥ 30 kg/m(2) at baseline. Over a mean 23.9 years of follow-up, 215 (8.8%) participants developed type 2 diabetes. The genotype score significantly predicted incident diabetes in all models, with an HR of 1.08 per risk allele (95% CI 1.04, 1.13) in the full model. The addition of the score to the full model modestly improved reclassification (continuous NRI 0.285; 95% CI 0.126, 0.433) but not discrimination (C statistics 0.824 and 0.829 in full models with and without score). Race-stratified analyses were similar.

CONCLUSIONS/INTERPRETATION

Knowledge of genotype predicts type 2 diabetes over 25 years in white and black young adults but may not improve prediction over routine clinical measurements.

Risk models and scores for type 2 diabetes: systematic review

OBJECTIVE

To evaluate current risk models and scores for type 2 diabetes and inform selection and implementation of these in practice.

DESIGN

Systematic review using standard (quantitative) and realist (mainly qualitative) methodology. Inclusion criteria Papers in any language describing the development or external validation, or both, of models and scores to predict the risk of an adult developing type 2 diabetes.

DATA SOURCES

Medline, PreMedline, Embase, and Cochrane databases were searched. Included studies were citation tracked in Google Scholar to identify follow-on studies of usability or impact.

DATA EXTRACTION

Data were extracted on statistical properties of models, details of internal or external validation, and use of risk scores beyond the studies that developed them. Quantitative data were tabulated to compare model components and statistical properties. Qualitative data were analysed thematically to identify mechanisms by which use of the risk model or score might improve patient outcomes.

RESULTS

8864 titles were scanned, 115 full text papers considered, and 43 papers included in the final sample. These described the prospective development or validation, or both, of 145 risk prediction models and scores, 94 of which were studied in detail here. They had been tested on 6.88 million participants followed for up to 28 years. Heterogeneity of primary studies precluded meta-analysis. Some but not all risk models or scores had robust statistical properties (for example, good discrimination and calibration) and had been externally validated on a different population. Genetic markers added nothing to models over clinical and sociodemographic factors. Most authors described their score as "simple" or "easily implemented," although few were specific about the intended users and under what circumstances. Ten mechanisms were identified by which measuring diabetes risk might improve outcomes. Follow-on studies that applied a risk score as part of an intervention aimed at reducing actual risk in people were sparse.

CONCLUSION

Much work has been done to develop diabetes risk models and scores, but most are rarely used because they require tests not routinely available or they were developed without a specific user or clear use in mind. Encouragingly, recent research has begun to tackle usability and the impact of diabetes risk scores. Two promising areas for further research are interventions that prompt lay people to check their own diabetes risk and use of risk scores on population datasets to identify high risk "hotspots" for targeted public health interventions.

Risk assessment tools for identifying individuals at risk of developing type 2 diabetes

Trials have demonstrated the preventability of type 2 diabetes through lifestyle modifications or drugs in people with impaired glucose tolerance. However, alternative ways of identifying people at risk of developing diabetes are required. Multivariate risk scores have been developed for this purpose. This article examines the evidence for performance of diabetes risk scores in adults by 1) systematically reviewing the literature on available scores and 2) their validation in external populations; and 3) exploring methodological issues surrounding the development, validation, and comparison of risk scores. Risk scores show overall good discriminatory ability in populations for whom they were developed. However, discriminatory performance is more heterogeneous and generally weaker in external populations, which suggests that risk scores may need to be validated within the population in which they are intended to be used. Whether risk scores enable accurate estimation of absolute risk remains unknown; thus, care is needed when using scores to communicate absolute diabetes risk to individuals. Several risk scores predict diabetes risk based on routine noninvasive measures or on data from questionnaires. Biochemical measures, in particular fasting plasma glucose, can improve prediction of such models. On the other hand, usefulness of genetic profiling currently appears limited.

Indian Diabetes Risk Score helps to distinguish type 2 from non-type 2 diabetes mellitus (GDRC-3)

AIM

The aim of this study was to investigate whether the Indian Diabetes Risk Score (IDRS) could assist in classifying type 2 diabetes mellitus (T2DM) and non-T2DM among patients attending clinics in India.

METHODS

Patient records from 2006 through 2009 were taken from the clinical database of a tertiary care diabetes hospital in Chennai, Southern India. A total of 8747 patients with diabetes, diagnosed by a physician either as type 1 diabetes mellitus (T1DM), T2DM, or other types were included for analysis. The IDRS, based on age, abdominal obesity, family history of diabetes, and physical activity, was calculated for each patient at first visit to our clinic. Receiver operating characteristic (ROC) curves were generated to obtain optimal IDRS cut points for predicting T2DM and non-T2DM.

RESULTS

Of the 8747 patient records analyzed, 204 (2.3%) were classified as non-T2DM and 8543 (97.7%) as T2DM. In ROC analysis, an IDRS ≥60 [area under the curve (AUC), 0.894; sensitivity, 83.8%; specificity, 81.0%] was predictive of T2DM, while an IDRS <60 (AUC, 0.882; sensitivity, 79.9%; specificity, 83.8%) was predictive of non-T2DM.

CONCLUSIONS

The IDRS, a simple, cost-effective risk score, can assist in classifying T2DM versus non-T2DM among clinic patients in India.

Identifying populations at high risk for diabetes with the Behavioral Risk Factor Surveillance System, Rhode Island, 2003

INTRODUCTION

We evaluated the feasibility of applying a previously validated diabetes risk score (DRS) to state-based surveillance data from the Behavioral Risk Factor Surveillance System (BRFSS) to assess population risk for developing type 2 diabetes or having undiagnosed type 2 diabetes.

METHODS

We conducted a cross-sectional analysis of 1,969 adults aged 30 to 60 years who self-reported never having been diagnosed with diabetes. The Danish DRS was applied to the 2003 Rhode Island BRFSS data by using 6 categorical variables: age, sex, body mass index, known hypertension, leisure-time physical activity, and family history of diabetes. The DRS was the sum of these individual scores, which ranged from 0 to 60; a score of 31 or more was considered high-risk.

RESULTS

We found that 436 study participants, representing 23% of Rhode Island adults aged 30 to 60 years, had a high DRS. In the final model, adults with at least some college education were 43% less likely to have a high DRS, compared to adults with a high school diploma. Adults with no health insurance were 54% more likely to have a high DRS compared with insured adults.

CONCLUSION

By adding a family history question in odd years to correspond to the hypertension module in the BRFSS, routinely available state-level surveys can be used with a DRS to monitor populations at high risk for developing type 2 diabetes. In Rhode Island, almost one-fourth of adults aged 30 to 60 years were at high risk for having undiagnosed diabetes or developing diabetes. Adults with lower education and without health insurance were at highest risk.

Evidence that prehypertension is a risk factor for Type 2 diabetes

Whether or not blood pressure categories below 140/90 mmHg are associated with incident Type 2 diabetes or cardiovascular disease is subject to debate. Currently, a blood pressure of 120-139/80-89 mmHg is recognized as prehypertension. This article evaluates the association of prehypertension with incident Type 2 diabetes in the San Antonio Heart study. The authors found that prehypertension in the entire cohort was not related to incident Type 2 diabetes in fully adjusted analyses, but that a blood pressure of 130-139/85-89 mmHg was related to incident diabetes. These results, and conclusions of other studies, suggest that the prehypertension category should be divided for diabetes risk assessment.