Effect of secular trends on age-related trajectories of cardiovascular risk factors: the Whitehall II longitudinal study 1985-2009

Secular trends in cardiovascular risk factors have been described, but few studies have examined simultaneously the effects of both ageing and secular trends within the same cohort

Heart Rate and Heart Rate Variability Changes Are Not Related to Future Cardiovascular Disease and Death in People With and Without Dysglycemia: A Downfall of Risk Markers? The Whitehall II Cohort Study

OBJECTIVE: Higher resting heart rate (rHR) and lower heart rate variability (HRV) are associated with increased risk of cardiovascular disease (CVD) and all-cause mortality in people with and without diabetes. It is unknown whether temporal changes in rHR and HRV may contribute to this risk. We investigated associations between 5-year changes in rHR and HRV and risk of future CVD and death, taking into account participants' baseline glycemic state. RESEARCH DESIGN AND METHODS: In this prospective, population-based cohort study we investigated 4,611 CVD-free civil servants (mean [SD] age, 60 [5.9] years; 70% men). We measured rHR and/or six indices of HRV. Associations of 5-year change in 5-min rHR and HRV with fatal and nonfatal CVD and all-cause mortality or the composite of the two were assessed, with adjustments made for relevant confounders. Effect modification by glycemic state was tested. RESULTS: At baseline, 63% of participants were normoglycemic, 29% had prediabetes, and 8% had diabetes. During a median (interquartile range) follow-up of 11.9 (11.4; 12.3) years, 298 participants (6.5%) experienced a CVD event and 279 (6.1%) died of non-CVD-related causes. We found no association between 5-year changes in rHR and HRV and future events. Only baseline rHR was associated with all-cause mortality. A 10 bpm-higher baseline HR level was associated with a 11.4% higher rate of all-cause mortality (95% CI 1.0-22.9%; P = 0.032). Glycemic state did not modify associations. CONCLUSIONS: Changes in rHR and HRV and possibly also baseline values of these measures are not associated with future CVD or death in people with or without dysglycemia

Age trajectories of glycaemic traits in non-diabetic South Asian and white individuals: the Whitehall II cohort study.

South Asian individuals have an increased prevalence of type 2 diabetes, but little is known about the development of glycaemic traits in this ethnic group. We compared age-related changes in glycaemic traits between non-diabetic South Asian and white participants

Trajectories of glycaemia, insulin sensitivity and insulin secretion in South Asian and white individuals before diagnosis of type 2 diabetes: a longitudinal analysis from the Whitehall II cohort study

$\textbf{AIMS/HYPOTHESIS}$: South Asian individuals have reduced insulin sensitivity and increased risk of type 2 diabetes compared with white individuals. Temporal changes in glycaemic traits during middle age suggest that impaired insulin secretion is a particular feature of diabetes development among South Asians. We therefore aimed to examine ethnic differences in early changes in glucose metabolism prior to incident type 2 diabetes. $\textbf{METHODS}$: In a prospective British occupational cohort, subject to 5 yearly clinical examinations, we examined ethnic differences in trajectories of fasting plasma glucose (FPG), 2 h post-load plasma glucose (2hPG), fasting serum insulin (FSI), 2 h post-load serum insulin (2hSI), HOMA of insulin sensitivity (HOMA2-S) and secretion (HOMA2-B), and the Gutt insulin sensitivity index (ISI$_{0,120}$) among 120 South Asian and 867 white participants who developed diabetes during follow-up (1991-2013). We fitted cubic mixed-effects models to longitudinal data with adjustment for a wide range of covariates. $\textbf{RESULTS}$: Compared with white individuals, South Asians had a faster increase in FPG before diagnosis (slope difference 0.22 mmol/l per decade; 95% CI 0.02, 0.42; p = 0.03) and a higher FPG level at diagnosis (0.27 mmol/l; 95% CI 0.06, 0.48; p = 0.01). They also had higher FSI and 2hSI levels before and at diabetes diagnosis. South Asians had a faster decline and lower HOMA2-S (log e -transformed) at diagnosis compared with white individuals (0.33; 95% CI 0.21, 0.46; p < 0.001). HOMA2-B increased in both ethnic groups until 7 years before diagnosis and then declined; the initial increase was faster in white individuals. ISI$_{0,120}$ declined steeply in both groups before diagnosis; levels were lower among South Asians before and at diagnosis. There were no ethnic differences in 2hPG trajectories. $\textbf{CONCLUSIONS/INTERPRETATION}$: We observed different trajectories of plasma glucose, insulin sensitivity and secretion prior to diabetes diagnosis in South Asian and white individuals. This might be due to ethnic differences in the natural history of diabetes. South Asian individuals experienced a more rapid decrease in insulin sensitivity and faster increases in FPG compared with white individuals. These findings suggest more marked disturbance in beta cell compensation prior to diabetes diagnosis in South Asian individuals.AH, RKS and DRW are supported by the Danish Diabetes Academy. The Danish Diabetes Academy is funded by the Novo Nordisk Foundation. RKS is further supported by the Aarhus Institute of Advanced Studies. KF is supported by the Novo Nordisk Foundation. EJB is supported by the British Heart Foundation (RG/13/2/30098). The UK Medical Research Council (MR/K013351/1; G0902037), the British Heart Foundation (RG/13/2/30098) and the US National Institutes of Health (R01HL36310, R01AG013196) have supported collection of data in the Whitehall II study

Heterogeneity in glucose response curves during an oral glucose tolerance test and associated cardiometabolic risk

We aimed to examine heterogeneity in glucose response curves during an oral glucose tolerance test with multiple measurements and to compare cardiometabolic risk profiles between identified glucose response curve groups. We analyzed data from 1,267 individuals without diabetes from five studies in Denmark, the Netherlands and the USA. Each study included between 5 and 11 measurements at different time points during a 2-h oral glucose tolerance test, resulting in 9,602 plasma glucose measurements. Latent class trajectories with a cubic specification for time were fitted to identify different patterns of plasma glucose change during the oral glucose tolerance test. Cardiometabolic risk factor profiles were compared between the identified groups. Using latent class trajectory analysis, five glucose response curves were identified. Despite similar fasting and 2-h values, glucose peaks and peak times varied greatly between groups, ranging from 7-12 mmol/L, and 35-70 min. The group with the lowest and earliest plasma glucose peak had the lowest estimated cardiovascular risk, while the group with the most delayed plasma glucose peak and the highest 2-h value had the highest estimated risk. One group, with normal fasting and 2-h values, exhibited an unusual profile, with the highest glucose peak and the highest proportion of smokers and men. The heterogeneity in glucose response curves and the distinct cardiometabolic risk profiles may reflect different underlying physiologies. Our results warrant more detailed studies to identify the source of the heterogeneity across the different phenotypes and whether these differences play a role in the development of type 2 diabetes and cardiovascular disease

Determinants of aortic stiffness: 16-year follow-up of the Whitehall II study.

Aortic stiffness is a strong predictor of cardiovascular disease endpoints. Cross-sectional studies have shown associations of various cardiovascular risk factors with aortic pulse wave velocity, a measure of aortic stiffness, but the long-term impact of these factors on aortic stiffness is unknown

Incidence of Diabetes in the Working Population in Spain: Results from the ICARIA Cohort

INTRODUCTION: Our objective was to evaluate the incidence of type 2 diabetes mellitus (T2DM) in a working population in Spain and to assess associations between its development and several risk factors. METHODS: The ICARIA (Ibermutuamur CArdiovascular RIsk Assessment) cohort (n = 627,523) includes ~3% of Spanish workers. This analysis was undertaken in individuals whose glycaemic status during the index period (May 2004-December 2007) was determined to be normal or indicative of prediabetes [fasting plasma glucose (FPG) 100-125 mg/dl] and who had at least one FPG measurement taken 9 months after a first measurement during follow-up (May 2004-June 2014) (n = 380,366). T2DM patients were defined as those with an FPG ? 126 mg/day and those who had already been diagnosed with T2DM or were taking antihyperglycaemic medications. RESULTS: The incidence rate of T2DM was 5.0 [95% confidence interval (CI) 4.9-5.1] cases per 1000 person-years. Under multivariate logistic regression analysis, the factor showing the strongest association with the occurrence of T2DM was the baseline FPG level, with the likelihood of T2DM almost doubling for every 5 mg/dl increase in baseline FPG between 100 and < 126 mg/dl. The presence of other cardiometabolic risk factors and being a blue-collar worker were also significantly associated with the occurrence of T2DM. CONCLUSIONS: The incidence of T2DM in the working population was within the range encountered in the general population and prediabetes was found to be the strongest risk factor for the development of diabetes. The workplace is an appropriate and feasible setting for the assessment of easily measurable risk factors, such as the presence of prediabetes and other cardiometabolic factors, to facilitate the early detection of individuals at higher risk of diabetes and the implementation of diabetes prevention programmes

Detrended Fluctuation Analysis in the prediction of type 2 diabetes mellitus in patients at risk: Model optimization and comparison with other metrics

[EN] Complexity analysis of glucose time series with Detrended Fluctuation Analysis (DFA) has been proved to be useful for the prediction of type 2 diabetes mellitus (T2DM) development. We propose a modified DFA algorithm, review some of its characteristics and compare it with other metrics derived from continuous glucose monitorization in this setting. Several issues of the DFA algorithm were evaluated: (1) Time windowing: the best predictive value was obtained including all time-windows from 15 minutes to 24 hours. (2) Influence of circadian rhythms: for 48-hour glucometries, DFA alpha scaling exponent was calculated on 24hour sliding segments (1-hour gap, 23-hour overlap), with a median coefficient of variation of 3.2%, which suggests that analysing time series of at least 24-hour length avoids the influence of circadian rhythms. (3) Influence of pretreatment of the time series through integration: DFA without integration was more sensitive to the introduction of white noise and it showed significant predictive power to forecast the development of T2DM, while the pretreated time series did not. (4) Robustness of an interpolation algorithm for missing values: The modified DFA algorithm evaluates the percentage of missing values in a time series. Establishing a 2% error threshold, we estimated the number and length of missing segments that could be admitted to consider a time series as suitable for DFA analysis. For comparison with other metrics, a Principal Component Analysis was performed and the results neatly tease out four different components. The first vector carries information concerned with variability, the second represents mainly DFA alpha exponent, while the third and fourth vectors carry essentially information related to the two "pre-diabetic behaviours" (impaired fasting glucose and impaired glucose tolerance). The scaling exponent obtained with the modified DFA algorithm proposed has significant predictive power for the development of T2DM in a high-risk population compared with other variability metrics or with the standard DFA algorithm.This study has been funded by Instituto de Salud Carlos III through the project PI17/00856 (Co-funded by the European Regional Development Fund, A way to make Europe). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Colás, A.; Vigil, L.; Vargas, B.; Cuesta Frau, D.; Varela, M. (2019). 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The community-based prevention of diabetes (ComPoD) study: A randomised, waiting list controlled trial of a voluntary sector-led diabetes prevention programme

© 2019 The Author(s). Objective: This two-site randomised trial compared the effectiveness of a voluntary sector-led, community-based diabetes prevention programme to a waiting-list control group at 6 months, and included an observational follow-up of the intervention arm to 12 months. Methods: Adults aged 18-75 years at increased risk of developing type 2 diabetes due to elevated blood glucose and being overweight were recruited from primary care practices at two UK sites, with data collected in participants' homes or community venues. Participants were randomised using an online central allocation service. The intervention, comprising the prototype "Living Well, Taking Control" (LWTC) programme, involved four weekly two-hour group sessions held in local community venues to promote changes in diet and physical activity, plus planned follow-up contacts at two, three, six, nine and 12 months alongside 5 hours of additional activities/classes. Waiting list controls received usual care for 6 months before accessing the programme. The primary outcome was weight loss at 6 months. Secondary outcomes included glycated haemoglobin (HbA1c), blood pressure, physical activity, diet, health status and well-being. Only researchers conducting analyses were blinded. Results: The target sample of 314 participants (157 each arm) was largely representative of local populations, including 44% men, 26% from ethnic minorities and 33% living in deprived areas. Primary outcome data were available for 285 (91%) participants (141 intervention, 144 control). Between baseline and 6 months, intervention participants on average lost more weight than controls (- 1.7 kg, 95% CI - 2.59 to - 0.85). Higher attendance was associated with greater weight loss (- 3.0 kg, 95% CI - 4.5 to - 1.5). The prototype LWTC programme more than doubled the proportion of participants losing > 5% of their body weight (21% intervention vs. 8% control, OR 2.83, 95% CI 1.36 to 5.90) and improved self-reported dietary behaviour and health status. There were no impacts on HbA1c, blood pressure, physical activity and well-being at 6 months and, amongst intervention participants, few further changes from six to 12-months (e.g. average weight re-gain 0.36 kg, 95% CI - 0.20 to 0.91). There were no serious adverse events but four exercise-related injuries were reported in the intervention arm. Conclusions: This voluntary sector-led diabetes prevention programme reached a broad spectrum of the population and had modest effects on weight-related outcomes, but limited impacts on other diabetes risk factors. Trial registration: Trial registration number: ISRCTN70221670, 5 September 2014 Funder (National Institute for Health Research School for Public Health Research) project reference number: SPHR-EXE-PES-COM