How good are GPs at adhering to a pragmatic trial protocol in primary care? Results from the ADDITION-Cambridge cluster-randomized pragmatic trial

Objective: To assess the fidelity of general practitioners’ (GP) adherence to a long term pragmatic trial protocol. Design: Retrospective analyses of electronic primary care records of participants in the pragmatic cluster-randomised ADDITION (Anglo-Danish-Dutch Study of Intensive Treatment In People with Screen Detected Diabetes in Primary Care)-Cambridge trial, comparing intensive multi-factorial treatment (IT) vs. routine care (RC). Data were collected from the date of diagnosis until December 2010. Setting: Primary care surgeries in the East of England Study sample/participants: A subsample (n=189, RC-arm: n=99, IT-arm: n=90) of patients from the ADDITION-Cambridge cohort (867 patients), consisting of 40-69 year old patients with screen detected diabetes mellitus. Interventions: In the RC-arm treatment was delivered according to concurrent treatment guidelines. Surgeries in the IT-arm received funding for additional contacts between GPs/nurses and patients, and GPs were advised to follow more intensive treatment algorithms for the management of glucose, lipids and blood pressure and aspirin therapy than in the RC-arm. Outcome measures: The number of annual contacts between patients and GPs/nurses, the proportion of patients receiving prescriptions for cardio-metabolic medication in years 1 to 5 after diabetes diagnosis, and the adherence to prescription algorithms. Results: The difference in the number of annual GP contacts (β=0.65) and nurse contacts (β=-0.15) between the study arms was small and insignificant. Patients in the IT-arm were more likely to receive glucose-lowering (OR=3.27), ACE-inhibiting (OR=2.03) and lipid-lowering drugs (OR=2.42, all p-values<0.01) than patients in the RC-arm. The prescription adherence varied between medication classes, but improved in both trial arms over the 5 year follow-up. Conclusions: The adherence of GPs to different aspects of the trial protocol was mixed. Background changes in health care policy need to be considered as they have the potential to dilute differences in treatment intensity and hence incremental effect. Clinical trial number: ISRCTN8676908

Change in physical activity after diagnosis of diabetes or hypertension: results from an observational population-based cohort study

Background: Chronic diseases like diabetes mellitus or hypertension are a major public health challenge. Irregular physical activity (PA) is one of the most important modifiable risk factors for chronic conditions and their complications. However, engaging in regular PA is a challenge for many individuals. The literature suggests that a diagnosis of a disease might serve as a promising point in time to change health behavior. This study investigates whether a diagnosis of diabetes or hypertension is associated with changes in PA. Methods: Analyses are based on 4261 participants of the population-based KORA S4 study (1999-2001) and its subsequent 7-and 14-year follow-ups. Information on PA and incident diagnoses of diabetes or hypertension was assessed via standardized interviews. Change in PA was regressed upon diagnosis with diabetes or hypertension, using logistic regression models. Models were stratified into active and inactive individuals at baseline to avoid ceiling and floor effects or regression to the mean. Results: Active participants at baseline showed higher odds (OR = 2.16 [1.20;3.89]) for becoming inactive after a diabetes diagnosis than those without a diabetes diagnosis. No other significant association was observed. Discussion: As PA is important for the management of diabetes or hypertension, ways to increase or maintain PA levels in newly-diagnosed patients are important. Communication strategies might be crucial, and practitioners and health insurance companies could play a key role in raising awareness

The impact of type 2 diabetes on health related quality of life in Bangladesh: results from a matched study comparing treated cases with non-diabetic controls

Background Little is known about the association between diabetes and health related quality of life (HRQL) in lower-middle income countries. This study aimed to investigate HRQL among individuals with and without diabetes in Bangladesh. Methods The analysis is based on data of a case-control study, including 591 patients with type 2 diabetes (cases) who attended an outpatient unit of a hospital in Dhaka and 591 age -and sex-matched individuals without diabetes (controls). Information about socio-demographic characteristics, health conditions, and HRQL were assessed in a structured interview. HRQL was measured with the EuroQol (EQ) visual analogue scale (VAS) and the EQ five-dimensional (5D) descriptive system. The association between diabetes status and quality of life was examined using multiple linear and logistic regression models. Results Mean EQ-VAS score of patients with diabetes was 11.5 points lower (95 %-CI: −13.5, −9.6) compared to controls without diabetes. Patients with diabetes were more likely to report problems in all EQ-5D dimensions than controls, with the largest effect observed in the dimensions ‘self-care’ (OR = 5.9; 95 %-CI: 2.9, 11.8) and ‘mobility’ (OR = 4.5; 95 %-CI: 3.0, −6.6). In patients with diabetes, male gender, high education, and high-income were associated with higher VAS score and diabetes duration and foot ulcer associated with lower VAS scores. Other diabetes-related complications were not significantly associated with HRQL. Conclusions Our findings suggest that the impact of diabetes on HRQL in the Bangladeshi population is much higher than what is known from western populations and that unlike in western populations comorbidities/complications are not the driving factor for this effect

advancing the evidence base for public policies impacting on dietary behaviour physical activity and sedentary behaviour in europe the policy evaluation network promoting a multidisciplinary approach

Abstract Non-communicable diseases (NCDs) are the leading cause of global mortality. As the social and economic costs of NCDs have escalated, action is needed to tackle important causes of many NCD's: low physical activity levels and unhealthy dietary behaviours. As these behaviours are driven by upstream factors, successful policy interventions are required that encourage healthy dietary behaviours, improve physical activity levels and reduce sedentary behaviours of entire populations. However, to date, no systematic research on the implementation and evaluation of policy interventions related to these health behaviours has been conducted across Europe. Consequently, no information on the merit, gaps, worth or utility of cross-European policy interventions is available, and no guidance or recommendations on how to enhance this knowledge across European countries exists. As part of the Joint Programming Initiative "A Healthy Diet for a Healthy Life" (JPI HDHL), 28 research institutes from seven European countries and New Zealand have combined their expertise to form the Policy Evaluation Network (PEN). PEN's aim is to advance tools to identify, evaluate, implement and benchmark policies designed to directly or indirectly target dietary behaviours, physical activity, and sedentary behaviour in Europe, as well as to understand how these policies increase or decrease health inequalities. Using well-defined evaluation principles and methods, PEN will examine the content, implementation and impact of policies addressing dietary behaviour, physical activity levels and sedentary behaviour across Europe. It will realise the first steps in a bespoke health policy monitoring and surveillance system for Europe, and refine our knowledge of appropriate research designs and methods for the quantification of policy impact. It will contribute to our understanding of how to achieve successful transnational policy implementation and monitoring of these policies in different cultural, demographic or socioeconomic settings. PEN will consider equity and diversity aspects to ensure that policy actions are inclusive and culturally sensitive. Finally, based on three policy cases, PEN will illustrate how best to evaluate the implementation and impact of such policies in order to yield healthy diets and activity patterns that result in healthier lives for all European citizens

Advancing the evidence base for public policies impacting on dietary behaviour, physical activity and sedentary behaviour in Europe: the Policy Evaluation Network promoting a multidisciplinary approach

Non-communicable diseases (NCDs) are the leading cause of global mortality. As the social and economic costs of NCDs have escalated, action is needed to tackle important causes of many NCD's: low physical activity levels and unhealthy dietary behaviours. As these behaviours are driven by upstream factors, successful policy interventions are required that encourage healthy dietary behaviours, improve physical activity levels and reduce sedentary behaviours of entire populations. However, to date, no systematic research on the implementation and evaluation of policy interventions related to these health behaviours has been conducted across Europe. Consequently, no information on the merit, gaps, worth or utility of cross-European policy interventions is available, and no guidance or recommendations on how to enhance this knowledge across European countries exists. As part of the Joint Programming Initiative "A Healthy Diet for a Healthy Life" (JPI HDHL), 28 research institutes from seven European countries and New Zealand have combined their expertise to form the Policy Evaluation Network (PEN). PEN's aim is to advance tools to identify, evaluate, implement and benchmark policies designed to directly or indirectly target dietary behaviours, physical activity, and sedentary behaviour in Europe, as well as to understand how these policies increase or decrease health inequalities. Using well-defined evaluation principles and methods, PEN will examine the content, implementation and impact of policies addressing dietary behaviour, physical activity levels and sedentary behaviour across Europe. It will realise the first steps in a bespoke health policy monitoring and surveillance system for Europe, and refine our knowledge of appropriate research designs and methods for the quantification of policy impact. It will contribute to our understanding of how to achieve successful transnational policy implementation and monitoring of these policies in different cultural, demographic or socioeconomic settings. PEN will consider equity and diversity aspects to ensure that policy actions are inclusive and culturally sensitive. Finally, based on three policy cases, PEN will illustrate how best to evaluate the implementation and impact of such policies in order to yield healthy diets and activity patterns that result in healthier lives for all European citizens

International travel-related control measures to contain the COVID-19 pandemic: a rapid review

BACKGROUND: In late 2019, the first cases of coronavirus disease 2019 (COVID‐19) were reported in Wuhan, China, followed by a worldwide spread. Numerous countries have implemented control measures related to international travel, including border closures, travel restrictions, screening at borders, and quarantine of travellers. OBJECTIVES: To assess the effectiveness of international travel‐related control measures during the COVID‐19 pandemic on infectious disease transmission and screening‐related outcomes. SEARCH METHODS: We searched MEDLINE, Embase and COVID‐19‐specific databases, including the Cochrane COVID‐19 Study Register and the WHO Global Database on COVID‐19 Research to 13 November 2020. SELECTION CRITERIA: We considered experimental, quasi‐experimental, observational and modelling studies assessing the effects of travel‐related control measures affecting human travel across international borders during the COVID‐19 pandemic. In the original review, we also considered evidence on severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS). In this version we decided to focus on COVID‐19 evidence only. Primary outcome categories were (i) cases avoided, (ii) cases detected, and (iii) a shift in epidemic development. Secondary outcomes were other infectious disease transmission outcomes, healthcare utilisation, resource requirements and adverse effects if identified in studies assessing at least one primary outcome. DATA COLLECTION AND ANALYSIS: Two review authors independently screened titles and abstracts and subsequently full texts. For studies included in the analysis, one review author extracted data and appraised the study. At least one additional review author checked for correctness of data. To assess the risk of bias and quality of included studies, we used the Quality Assessment of Diagnostic Accuracy Studies (QUADAS‐2) tool for observational studies concerned with screening, and a bespoke tool for modelling studies. We synthesised findings narratively. One review author assessed the certainty of evidence with GRADE, and several review authors discussed these GRADE judgements. MAIN RESULTS: Overall, we included 62 unique studies in the analysis; 49 were modelling studies and 13 were observational studies. Studies covered a variety of settings and levels of community transmission. Most studies compared travel‐related control measures against a counterfactual scenario in which the measure was not implemented. However, some modelling studies described additional comparator scenarios, such as different levels of stringency of the measures (including relaxation of restrictions), or a combination of measures. Concerns with the quality of modelling studies related to potentially inappropriate assumptions about the structure and input parameters, and an inadequate assessment of model uncertainty. Concerns with risk of bias in observational studies related to the selection of travellers and the reference test, and unclear reporting of certain methodological aspects. Below we outline the results for each intervention category by illustrating the findings from selected outcomes. Travel restrictions reducing or stopping cross‐border travel (31 modelling studies) The studies assessed cases avoided and shift in epidemic development. We found very low‐certainty evidence for a reduction in COVID‐19 cases in the community (13 studies) and cases exported or imported (9 studies). Most studies reported positive effects, with effect sizes varying widely; only a few studies showed no effect. There was very low‐certainty evidence that cross‐border travel controls can slow the spread of COVID‐19. Most studies predicted positive effects, however, results from individual studies varied from a delay of less than one day to a delay of 85 days; very few studies predicted no effect of the measure. Screening at borders (13 modelling studies; 13 observational studies) Screening measures covered symptom/exposure‐based screening or test‐based screening (commonly specifying polymerase chain reaction (PCR) testing), or both, before departure or upon or within a few days of arrival. Studies assessed cases avoided, shift in epidemic development and cases detected. Studies generally predicted or observed some benefit from screening at borders, however these varied widely. For symptom/exposure‐based screening, one modelling study reported that global implementation of screening measures would reduce the number of cases exported per day from another country by 82% (95% confidence interval (CI) 72% to 95%) (moderate‐certainty evidence). Four modelling studies predicted delays in epidemic development, although there was wide variation in the results between the studies (very low‐certainty evidence). Four modelling studies predicted that the proportion of cases detected would range from 1% to 53% (very low‐certainty evidence). Nine observational studies observed the detected proportion to range from 0% to 100% (very low‐certainty evidence), although all but one study observed this proportion to be less than 54%. For test‐based screening, one modelling study provided very low‐certainty evidence for the number of cases avoided. It reported that testing travellers reduced imported or exported cases as well as secondary cases. Five observational studies observed that the proportion of cases detected varied from 58% to 90% (very low‐certainty evidence). Quarantine (12 modelling studies) The studies assessed cases avoided, shift in epidemic development and cases detected. All studies suggested some benefit of quarantine, however the magnitude of the effect ranged from small to large across the different outcomes (very low‐ to low‐certainty evidence). Three modelling studies predicted that the reduction in the number of cases in the community ranged from 450 to over 64,000 fewer cases (very low‐certainty evidence). The variation in effect was possibly related to the duration of quarantine and compliance. Quarantine and screening at borders (7 modelling studies; 4 observational studies) The studies assessed shift in epidemic development and cases detected. Most studies predicted positive effects for the combined measures with varying magnitudes (very low‐ to low‐certainty evidence). Four observational studies observed that the proportion of cases detected for quarantine and screening at borders ranged from 68% to 92% (low‐certainty evidence). The variation may depend on how the measures were combined, including the length of the quarantine period and days when the test was conducted in quarantine. AUTHORS' CONCLUSIONS: With much of the evidence derived from modelling studies, notably for travel restrictions reducing or stopping cross‐border travel and quarantine of travellers, there is a lack of 'real‐world' evidence. The certainty of the evidence for most travel‐related control measures and outcomes is very low and the true effects are likely to be substantially different from those reported here. Broadly, travel restrictions may limit the spread of disease across national borders. Symptom/exposure‐based screening measures at borders on their own are likely not effective; PCR testing at borders as a screening measure likely detects more cases than symptom/exposure‐based screening at borders, although if performed only upon arrival this will likely also miss a meaningful proportion of cases. Quarantine, based on a sufficiently long quarantine period and high compliance is likely to largely avoid further transmission from travellers. Combining quarantine with PCR testing at borders will likely improve effectiveness. Many studies suggest that effects depend on factors, such as levels of community transmission, travel volumes and duration, other public health measures in place, and the exact specification and timing of the measure. Future research should be better reported, employ a range of designs beyond modelling and assess potential benefits and harms of the travel‐related control measures from a societal perspective

Dietary behaviour and physical activity policies in Europe: learnings from the Policy Evaluation Network (PEN)

The European Policy Evaluation Network (PEN), initiated in autumn 2018, aimed at advancing the evidence base for public policies impacting dietary behaviour, physical activity and sedentary behaviours in Europe. This is needed because non-communicable diseases-the leading cause of global mortality-are substantially caused by physical inactivity and unhealthy dietary behaviours, which in turn are driven by upstream factors that have not yet been addressed effectively by prevention approaches. Thus, successful policy interventions are required that target entire populations and tackle the 'causes of the causes'. To advance our knowledge on the effective implementation of policies and their impact in terms of improving health behaviours, PEN focused on five research tasks: (i) Adaptation and implementation of a Food Environment Policy Index (Food-EPI) and development of a Physical Activity Environment Policy Index (PA-EPI); (ii) Mapping of health-related indicators needed for policy evaluation and facilitating a harmonized pan-European approach for surveillance to assess the impact of policy interventions; (iii) Refining quantitative methods to evaluate the impact of public policies; (iv) Identifying key barriers and facilitators of implementation of policies; and (v) Advance understanding the equity impact of the development, implementation and evaluation of policies aimed at promoting physical activity and a healthy diet. Finally, and in order to provide concrete evidence for policymaking, existing exemplary policies, namely sugar-sweetened beverages taxation, active transport policies and school policies on nutrition and physical activity were assessed in consideration of these five tasks. At the end of the PEN project's formal runtime, considerable advancements have been made. Here, we present an overview of the most important learnings and outputs

Gesundheitsökonomische Evaluation von Präventions- und Managementstrategien bei Diabetes.

HintergrundRessourcen im Gesundheitswesen sind knapp, und die Entscheidung für oder gegen eine bestimmte Strategie verursacht Opportunitätskosten. Aufgrund der hohen Versorgungskosten ist die Frage nach der effizienten Verwendung von Ressourcen bei der Betrachtung von Diabetes von besonderer Bedeutung. Mit der systematischen Gegenüberstellung von Kosten und Gesundheitseffekten bietet die gesundheitsökonomische Evaluation (GÖE) einen fundierten Rahmen, der zur Beantwortung dieser Frage beitragen kann.Ziel der ArbeitAnhand des Beispiels Diabetes wird ein Überblick über die Methodik der GÖE präsentiert, um das Verständnis für die Relevanz wissenschaftlicher Studien zu verbessern.Material und MethodenDie Kosten-Nutzwert-Analyse stellt die häufigste Form der Effizienzbewertung in der Literatur dar. Sie sieht für den Vergleich alternativer Handlungsoptionen eine Gegenüberstellung von Kosten und Gesundheitseffekten vor. In der Praxis werden bei der GÖE hierzu oft Daten aus klinischen Studien durch modellbasierte Simulationsstudien ergänzt; wichtig bei Diabetes sind zudem ein langfristiger Zeithorizont unter Berücksichtigung von Diskontierung sowie die vollständige Erfassung aller relevanten Kostenarten.Ergebnisse und DiskussionLaut größtenteils internationaler Evidenz sind eine intensivierte Kontrolle von Blutdruck und Blutzuckerspiegel sowie verhältnispräventive Maßnahmen für die Diabetesprävention mit hoher Wahrscheinlichkeit kosteneffektive bzw. effektive und kostengünstige Strategien. Bei der Allokation von Ressourcen sind auch viele andere Aspekte von Bedeutung, und Effizienzüberlegungen spielen im deutschen Gesundheitssystem nur eine nachgeordnete Rolle. Um das Potenzial der GÖE auszuschöpfen, ist es wichtig, die Gesundheitsökonomie bereits in der Planungsphase von Studien mit einzubeziehen