Patient-centred care, health behaviours and cardiovascular risk factor levels in people with recently diagnosed type 2 diabetes: 5-year follow-up of the ADDITION-Plus trial cohort.

OBJECTIVE: To examine the association between the experience of patient-centred care (PCC), health behaviours and cardiovascular disease (CVD) risk factor levels among people with type 2 diabetes. DESIGN: Population-based prospective cohort study. SETTING: 34 general practices in East Anglia, UK, delivering organised diabetes care. PARTICIPANTS: 478 patients recently diagnosed with type 2 diabetes aged between 40 and 69 years enrolled in the ADDITION-Plus trial. MAIN OUTCOME MEASURES: Self-reported and objectively measured health behaviours (diet, physical activity, smoking status), CVD risk factor levels (blood pressure, lipid levels, glycated haemoglobin, body mass index, waist circumference) and modelled 10-year CVD risk. RESULTS: Better experiences of PCC early in the course of living with diabetes were not associated with meaningful differences in self-reported physical activity levels including total activity energy expenditure (β-coefficient: 0.080 MET h/day (95% CI 0.017 to 0.143; p=0.01)), moderate-to-vigorous physical activity (β-coefficient: 5.328 min/day (95% CI 0.796 to 9.859; p=0.01)) and reduced sedentary time (β-coefficient: -1.633 min/day (95% CI -2.897 to -0.368; p=0.01)). PCC was not associated with clinically meaningful differences in levels of high-density lipoprotein cholesterol (β-coefficient: 0.002 mmol/L (95% CI 0.001 to 0.004; p=0.03)), systolic blood pressure (β-coefficient: -0.561 mm Hg (95% CI -0.653 to -0.468; p=0.01)) or diastolic blood pressure (β-coefficient: -0.565 mm Hg (95% CI -0.654 to -0.476; p=0.01)). Over an extended follow-up of 5 years, we observed no clear evidence that PCC was associated with self-reported, clinical or biochemical outcomes, except for waist circumference (β-coefficient: 0.085 cm (95% CI 0.015 to 0.155; p=0.02)). CONCLUSIONS: We found little evidence that experience of PCC early in the course of diabetes was associated with clinically important changes in health-related behaviours or CVD risk factors. TRIAL REGISTRATION NUMBER: ISRCTN99175498; Post-results.The trial is supported by the Medical Research Council (grant reference no: G0001164 ), the Wellcome Trust (grant reference no: G061895 ),Diabetes UK and National Health Service R&D support funding . SJG is a member of the National Institute for Health Research (NIHR) School for Primary Care Research. The General Practice and Primary Care Research Unit was supported by NIHR Research funds. ATP is supported by the NIHR Biomedical Research Centre at Guy’s and St Thomas’ NHS Foundation Trust and King’s College London. The views expressed in this publication are those of the authors and not necessarily those of the Department of Health.This is the final version of the article. It was first available from BMJ via http://dx.doi.org/10.1136/bmjopen-2015-00893

Sleep duration and cardiometabolic risk factors among individuals with type 2 diabetes.

OBJECTIVE: To examine the association between sleep duration and cardiometabolic risk factors among individuals with recently diagnosed type 2 diabetes (n = 391). METHODS: Sleep duration was derived using a combination of questionnaire and objective heart rate and movement sensing in the UK ADDITION-Plus study (2002-2007). Adjusted means were estimated for individual cardiometabolic risk factors and clustered cardiometabolic risk (CCMR) by five categories of sleep duration. RESULTS: We observed a J-shaped association between sleep duration and CCMR - individuals sleeping 7 to <8 h had a significantly better CCMR profile than those sleeping ≥9 h. Independent of physical activity and sedentary time, individuals sleeping 7 to <8 h had lower triacylglycerol (0.62 mmol/l (0.29, 1.06)) and higher high-density lipoprotein (HDL)-cholesterol levels (0.23 mmol/l (0.16, 0.30)) compared with those sleeping ≥9 h, and a lower waist circumference (7.87 cm (6.06, 9.68)) and body mass index (BMI) (3.47 kg/m(2) (2.69, 4.25)) than those sleeping <6 h. Although sleeping 7 to <8 h was associated with lower levels of systolic and diastolic blood pressure, HbA1c, total cholesterol, and low-density lipoprotein (LDL)-cholesterol, these associations were not statistically significant. CONCLUSIONS: Sleep duration has a J-shaped association with CCMR in individuals with diabetes, independent of potential confounding. Health promotion interventions might highlight the importance of adequate sleep in this high-risk population.The trial is supported by the Wellcome Trust, the Medical Research Council, Diabetes UK and National Health Service R&D support funding. SJG was a member of the National Institute for Health Research (NIHR) School for Primary Care Research. The General Practice and Primary Care Research Unit was supported by NIHR Research funds. SJG received support from the Department of Health NIHR Programme Grant funding scheme [RP-PG-0606-1259]. ATP is supported by the NIHR Biomedical Research Centre at Guy’s and St Thomas’ NHS Foundation Trust and King’s College London.This is the author accepted manuscript. The final version is available from Elsevier via http://dx.doi.org/10.1016/j.sleep.2014.10.00

Who will increase their physical activity? Predictors of change in objectively measured physical activity over 12 months in the ProActive cohort.

BACKGROUND: The aim was to identify predictors of change in objectively measured physical activity over 12 months in the ProActive cohort to improve understanding of factors influencing change in physical activity. METHODS: ProActive is a physical activity promotion trial that took place in Eastern England (1999-2004). 365 offspring of people with type 2 diabetes underwent measurement of physical activity energy expenditure (PAEE) using heart rate monitoring, fitness, and anthropometric and biochemical status at baseline and 1 year (n = 321). Linear regression was used to quantify the associations between baseline demographic, clinical, psychosocial and behavioural variables and change in PAEE over 12 months. This study is registered as ISRCTN61323766. RESULTS: ProActive participants significantly increased their PAEE by 0.6 kj/min (SD 4.2, p = 0.006) over one year, the equivalent of around 20 minutes brisk walking/day. Male sex and higher fitness at baseline predicted increase in PAEE. No significant associations were found for any other variables. Very few baseline demographic, clinical, psychosocial and behavioural predictors were associated with change in objectively measured physical activity. CONCLUSIONS: Traditional baseline determinants of self-reported physical activity targeted by behavioural interventions may be relatively weak predictors of change in objectively measured physical activity. Further research is needed to improve our understanding of factors influencing change in physical activity to inform the development and targeting of interventions.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Estimating the population impact of screening strategies for identifying and treating people at high risk of cardiovascular disease: modelling study

Objective To estimate the potential population impact of different screening strategies for identifying and treating people at high risk of cardiovascular disease, including strategies using routine data for cardiovascular risk stratification, in light of the UK government’s recommended national strategy to screen all adults aged 40-74 for cardiovascular risk

Which behavior change techniques are associated with changes in physical activity, diet and BMI in people with recently diagnosed diabetes?

Peer reviewe

The Relationship between Health Literacy and Health Behaviour in People with Diabetes: A Danish Population-Based Study.

Background. People with diabetes who have poor health behaviours are at greater risk for a range of adverse health outcomes. We aimed to investigate the relationship between health literacy and health behaviour (smoking, alcohol, physical activity, and diet) in people with diabetes. Methods. The study was based on respondents aged 25 years or older from a population-based survey in 2013 who reported having diabetes (n = 1685). Two dimensions from the Health Literacy Questionnaire were used: "understand health information" and "actively engage with healthcare providers." We used logistic regression to examine the association between health literacy and health behaviour. Results. After adjustment for sociodemographic factors, individuals with diabetes who found it difficult to understand information about health had higher odds of being physically inactive (OR: 3.43, 95% CI: 2.14-5.51) and having unhealthy dietary habits (OR: 3.01, 95% CI: 1.63-5.58). Similar results were observed for individuals who found it difficult to actively engage with healthcare providers. No associations were found between the two dimensions of health literacy and smoking and alcohol consumption. Conclusion. When developing health services and interventions to improve health behaviour among people with diabetes, our results suggest that they may benefit by including focus on health literacy.Peer Reviewe

The association of cycling with all-cause, cardiovascular and cancer mortality: findings from the population-based EPIC-Norfolk cohort.

OBJECTIVES: To investigate associations between modest levels of total and domain-specific (commuting, other utility, recreational) cycling and mortality from all causes, cardiovascular disease and cancer. DESIGN: Population-based cohort study (European Prospective Investigation into Cancer and Nutrition study-Norfolk). SETTING: Participants were recruited from general practices in the east of England and attended health examinations between 1993 and 1997 and again between 1998 and 2000. At the first health assessment, participants reported their average weekly duration of cycling for all purposes using a simple measure of physical activity. At the second health assessment, participants reported a more detailed breakdown of their weekly cycling behaviour using the EPAQ2 physical activity questionnaire. PARTICIPANTS: Adults aged 40-79 years at the first health assessment. PRIMARY OUTCOME MEASURE: All participants were followed for mortality (all-cause, cardiovascular and cancer) until March 2011. RESULTS: There were 22 450 participants with complete data at the first health assessment, of whom 4398 died during follow-up; and 13 346 participants with complete data at the second health assessment, of whom 1670 died during follow-up. Preliminary analyses using exposure data from the first health assessment showed that cycling for at least 60 min/week in total was associated with a 9% reduced risk of all-cause mortality (adjusted HR 0.91, 95% CI 0.84 to 0.99). Using the more precise measures of cycling available from the second health assessment, all types of cycling were associated with greater total moderate-to-vigorous physical activity; however, there was little evidence of an association between overall or domain-specific cycling and mortality. CONCLUSIONS: Cycling, in particular for utility purposes, was associated with greater moderate-to-vigorous and total physical activity. While this study provides tentative evidence that modest levels of cycling may reduce the risk of mortality, further research is required to confirm how much cycling is sufficient to induce health benefits

Medication burden in the first 5 years following diagnosis of type 2 diabetes: findings from the ADDITION-UK trial cohort.

INTRODUCTION: Individuals with screen-detected diabetes are likely to receive intensified pharmacotherapy to improve glycaemic control and general cardiometabolic health. Individuals are often asymptomatic, and little is known about the degree to which polypharmacy is present both before, and after diagnosis. We aimed to describe and characterize the pharmacotherapy burden of individuals with screen-detected diabetes at diagnosis, 1 and 5 years post-diagnosis. METHODS: The prescription histories of 1026 individuals with screen-detected diabetes enrolled in the ADDITION-UK trial of the promotion of intensive treatment were coded into general medication types at diagnosis, 1 and 5 years post-diagnosis. The association between change in the count of several medication types and age, baseline 10-year UK Prospective Diabetes Study (UKPDS) cardiovascular disease (CVD risk), sex, intensive treatment group and number of medications was explored. RESULTS: Just under half of individuals were on drugs unrelated to cardioprotection before diagnosis (42%), and this increased along with a rise in the number of prescribed diabetes-related and cardioprotective drugs. The medication profile over the first 5 years suggests multimorbidity and polypharmacy is present in individuals with screen-detected diabetes. Higher modeled CVD risk at baseline was associated with a greater increase in cardioprotective and diabetes-related medication, but not an increase in other medications. CONCLUSION: As recommended in national guidelines, our results suggest that treatment of diabetes was influenced by the underlying risk of CVD. While many individuals did not start glucose lowering and cardioprotective therapies in the first 5 years after diagnosis, more information is required to understand whether this represents unmet need, or patient-centered care. TRIAL REGISTRATION NUMBER: CNT00237549.This study was supported by the Welcome Trust (grant number G061895), the Medical Research Council (Grant numbers G0001164 and MC_UU_12015/4) and the National Institute for Health Research (Grant number RP-PG-0606-1259).This is the final version of the article. It first appeared from BMJ via http://dx.doi.org/10.1136/bmjdrc-2014-00007