No abstract

ObjeCtivesTo assess diagnostic accuracy of screening tests for pre-diabetes and efficacy of interventions (lifestyle or metformin) in preventing onset of type 2 diabetes in people with pre-diabetes. DesignSystematic review and meta-analysis. Data sOurCes anD methODMedline, PreMedline, and Embase. Study protocols and seminal papers were citation-tracked in Google Scholar to identify definitive trials and additional publications. Data on study design, methods, and findings were extracted onto Excel spreadsheets; a 20% sample was checked by a second researcher. Data extracted for screening tests included diagnostic accuracy and population prevalence. Two metaanalyses were performed, one summarising accuracy of screening tests (with the oral glucose tolerance test as the standard) for identification of pre-diabetes, and the other assessing relative risk of progression to type 2 diabetes after either lifestyle intervention or treatment with metformin.eligibility Criteria Empirical studies evaluating accuracy of tests for identification of pre-diabetes. Interventions (randomised trials and interventional studies) with a control group in people identified through screening. No language restrictions. results 2874 titles were scanned and 148 papers (covering 138 studies) reviewed in full. The final analysis included 49 studies of screening tests (five of which were prevalence studies) and 50 intervention trials. HbA 1c had a mean sensitivity of 0.49 (95% confidence interval 0.40 to 0.58) and specificity of 0.79 (0.73 to 0.84), for identification of pre-diabetes, though different studies used different cut-off values. Fasting plasma glucose had a mean sensitivity of 0.25 (0.19 to 0.32) and specificity of 0.94 (0.92 to 0.96). Different measures of glycaemic abnormality identified different subpopulations (for example, 47% of people with abnormal HbA 1c had no other glycaemic abnormality). Lifestyle interventions were associated with a 36% (28% to 43%) reduction in relative risk of type 2 diabetes over six months to six years, attenuating to 20% (8% to 31%) at follow-up in the period after the trails. COnClusiOnsHbA 1c is neither sensitive nor specific for detecting pre-diabetes; fasting glucose is specific but not sensitive. Interventions in people classified through screening as having pre-diabetes have some efficacy in preventing or delaying onset of type 2 diabetes in trial populations. As screening is inaccurate, many people will receives an incorrect diagnosis and be referred on for interventions while others will be falsely reassured and not offered the intervention. These findings suggest that "screen and treat" policies alone are unlikely to have substantial impact on the worsening epidemic of type 2 diabetes. registratiOn PROSPERO (No CRD42016042920).

Pooled results suggest that a variety of interventions can improve adherence. The clinical relevance of this improvement, highlighted by uncertain and inconsistent impact on clinical outcomes such as quality of life and asthma control, is less clear. We have low to moderate confidence in these findings owing to concerns about risk of bias and inconsistency. Future studies would benefit from predefining an evidence-based 'cut-off' for acceptable adherence and using objective adherence measures and validated tools and questionnaires. When possible, covert monitoring and some form of blinding or active control may help disentangle effects of the intervention from effects of inclusion in an adherence trial.

Prophylactic antibiotic therapy for chronic obstructive pulmonary disease (COPD).

This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in ; Vol. 22, No. 37. See the NIHR Journals Library website for further project information.

BackgroundThe majority of mid-life and older adults in the UK are not achieving recommended physical activity levels and inactivity is associated with many health problems. Walking is a safe, appropriate exercise. The PACE-UP trial sought to increase walking through the structured use of a pedometer and handbook, with and without support from a practice nurse trained in behaviour change techniques (BCTs). Understanding barriers and facilitators to engagement with a primary care based physical activity intervention is essential for future trials and programmes.MethodsWe conducted semi-structured telephone interviews using a topic guide with purposive samples of participants who did and did not increase their walking from both intervention groups. Interviews were audio-recorded, transcribed and coded independently by researchers prior to performing a thematic analysis. Responsiveness to the specific BCTs used was also analysed.ResultsForty-three trial participants were interviewed in early 2014. Almost all felt they had benefitted, irrespective of their change in step-count, and that primary care was an appropriate setting.Important facilitators included a desire for a healthy lifestyle, improved physical health, enjoyment of walking in the local environment, having a flexible routine allowing for an increase in walking, appropriate self and external monitoring and support from others.Important barriers included physical health problems, an inflexible routine, work and other commitments, the weather and a mistrust of the monitoring equipment.BCTs that were reported to have the most impact included: providing information about behaviour-health link; prompting self-monitoring and review of goals and outcomes; providing feedback; providing specific information about how to increase walking; planning social support/change; and relapse prevention. Rewards were unhelpful.ConclusionsDespite our expectation that there would be a difference between the experiences of those who did and did not objectively increase their walking, we found that most participants considered themselves to have succeeded in the trial and benefitted from taking part. Barriers and facilitators were similar across demographic groups and trial outcomes. Findings indicated several BCTs on which PA trial and programme planners could focus efforts with the expectation of greatest impact as well as strong support for primary care as an appropriate venue.Trial registrationISRCTN98538934.

BackgroundUrbanisation has been associated with temporal and geographical differences in asthma prevalence in low-income and middle-income countries (LMICs). However, little is known of the mechanisms by which urbanisation and asthma are associated, perhaps explained by the methodological approaches used to assess the urbanisation-asthma relationship.ObjectiveThis review evaluated how epidemiological studies have assessed the relationship between asthma and urbanisation in LMICs, and explored urban/rural differences in asthma prevalence.MethodsAsthma studies comparing urban/rural areas, comparing cities and examining intraurban variation were assessed for eligibility. Included publications were evaluated for methodological quality and pooled OR were calculated to indicate the risk of asthma in urban over rural areas.ResultsSeventy articles were included in our analysis. Sixty-three compared asthma prevalence between urban and rural areas, five compared asthma prevalence between cities and two examined intraurban variation in asthma prevalence. Urban residence was associated with a higher prevalence of asthma, regardless of asthma definition: current-wheeze OR:1.46 (95% CI:1.22 to 1.74), doctor diagnosis OR:1.89 (95% CI:1.47 to 2.41), wheeze-ever OR:1.44 (95% CI:1.15 to 1.81), self-reported asthma OR:1.77 (95% CI:1.33 to 2.35), asthma questionnaire OR:1.52 (95% CI:1.06 to 2.16) and exercise challenge OR:1.96 (95% CI:1.32 to 2.91).ConclusionsMost evidence for the relationship between urbanisation and asthma in LMICs comes from studies comparing urban and rural areas. These studies tend to show a greater prevalence of asthma in urban compared to rural populations. However, these studies have been unable to identify which specific characteristics of the urbanisation process may be responsible. An approach to understand how different dimensions of urbanisation, using contextual household and individual indicators, is needed for a better understanding of how urbanisation affects asthma.PROSPERO registration numberCRD42017064470.

No abstract