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Background Adapting interventions that have worked elsewhere can save resources associated with developing new interventions for each specific context. While a developing body of evidence shows benefits of adapted interventions compared with interventions transported without adaptation, there are also examples of interventions which have been extensively adapted, yet have not worked in the new context. Decisions on when, to what extent, and how to adapt interventions therefore are not straightforward, particularly when conceptualising intervention effects as contingent upon contextual interactions in complex systems. No guidance currently addresses these questions comprehensively. To inform development of an overarching guidance on adaptation of complex population health interventions, this systematic review synthesises the content of the existing guidance papers. Methods We searched for papers published between January 2000 and October 2018 in 7 bibliographic databases. We used citation tracking and contacted authors and experts to locate further papers. We double screened all the identified records. We extracted data into the following categories: descriptive information, key concepts and definitions, rationale for adaptation, aspects of adaptation, process of adaptation, evaluating and reporting adapted interventions. Data extraction was conducted independently by two reviewers, and retrieved data were synthesised thematically within pre-specified and emergent categories. Results We retrieved 6694 unique records. Thirty-eight papers were included in the review representing 35 sources of guidance. Most papers were developed in the USA in the context of implementing evidence-informed interventions among different population groups within the country, such as minority populations. We found much agreement on how the papers defined key concepts, aims, and procedures of adaptation, including involvement of key stakeholders, but also identified gaps in scope, conceptualisation, and operationalisation in several categories. Conclusions Our review found limitations that should be addressed in future guidance on adaptation . Specifically, future guidance needs to be reflective of adaptations in the context of transferring interventions across countries, including macro- (e.g. national-) level interventions, better theorise the role of intervention mechanisms and contextual interactions in the replicability of effects and accordingly conceptualise key concepts, such as fidelity to intervention functions, and finally, suggest evidence-informed strategies for adaptation re-evaluation and reporting. Trial registration PROSPERO 2018, CRD42018112714 .

Despite smaller effect sizes, interventions delivered at population level to prevent non-communicable diseases generally have greater reach, impact and equity than those delivered to high-risk groups. Nevertheless, how to shift population behaviour patterns in this way remains one of the greatest uncertainties for research and policy. Evidence about behaviour change interventions that are easier to evaluate tends to overshadow that for population-wide and system-wide approaches that generate and sustain healthier behaviours. Population health interventions are often implemented as natural experiments, which makes their evaluation more complex and unpredictable than a typical randomised controlled trial (RCT). We discuss the growing importance of evaluating natural experiments and their distinctive contribution to the evidence for public health policy. We contrast the established evidence-based practice pathway, in which RCTs generate ‘definitive’ evidence for particular interventions, with a practice-based evidence pathway in which evaluation can help adjust the compass bearing of existing policy. We propose that intervention studies should focus on reducing critical uncertainties, that non-randomised study designs should be embraced rather than tolerated and that a more nuanced approach to appraising the utility of diverse types of evidence is required. The complex evidence needed to guide public health action is not necessarily the same as that which is needed to provide an unbiased effect size estimate. The practice-based evidence pathway is neither inferior nor merely the best available when all else fails. It is often the only way to generate meaningful evidence to address critical questions about investing in population health interventions.

Background Data-driven population segmentation analysis utilizes data analytics to divide a heterogeneous population into parsimonious and relatively homogenous groups with similar healthcare characteristics. It is a promising patient-centric analysis that enables effective integrated healthcare interventions specific for each segment. Although widely applied, there is no systematic review on the clinical application of data-driven population segmentation analysis. Methods We carried out a systematic literature search using PubMed, Embase and Web of Science following PRISMA criteria. We included English peer-reviewed articles that applied data-driven population segmentation analysis on empirical health data. We summarized the clinical settings in which segmentation analysis was applied, compared and contrasted strengths, limitations, and practical considerations of different segmentation methods, and assessed the segmentation outcome of all included studies. The studies were assessed by two independent reviewers. Results We retrieved 14,514 articles and included 216 articles. Data-driven population segmentation analysis was widely used in different clinical contexts. 163 studies examined the general population while 53 focused on specific population with certain diseases or conditions, including psychological, oncological, respiratory, cardiovascular, and gastrointestinal conditions. Variables used for segmentation in the studies are heterogeneous. Most studies ( n  = 170) utilized secondary data in community settings ( n  = 185). The most common segmentation method was latent class/profile/transition/growth analysis ( n  = 96) followed by K-means cluster analysis ( n  = 60) and hierarchical analysis ( n  = 50), each having its advantages, disadvantages, and practical considerations. We also identified key criteria to evaluate a segmentation framework: internal validity, external validity, identifiability/interpretability, substantiality, stability, actionability/accessibility, and parsimony. Conclusions Data-driven population segmentation has been widely applied and holds great potential in managing population health. The evaluations of segmentation outcome require the interplay of data analytics and subject matter expertise. The optimal framework for segmentation requires further research.

\"Over recent decades, population ageing has become a truly global issue and has increasingly moved to the centre of public attention. Leading international experts in the political and social sciences, demography and history analyse the political and social consequences of demographic ageing. Together the contributions offer three main observations. First, the steadily-rising share of retirees has put pension systems under increasing pressure and has provoked profound pension reforms in many industrialized countries. Second, ageing societies experience significant changes both in the established patterns of transition from work to retirement as well as in the traditional concepts of retirement and old age. Third, running alongside the shift in the balance between younger and older people, the questions of generational justice have increasingly gained prominence in the Western world. This book is essential reading for all those concerned with the profound challenges faced by an ageing world\"-- Provided by publisher.

Japan has entered the era of super-ageing and advanced health transition, which is increasingly putting pressure on the sustainability of its health system. The level and pace of this health transition might vary across regions within Japan and concern is growing about increasing regional variations in disease burden. The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015) provides a comprehensive, comparable framework. We used data from GBD 2015 with the aim to quantify the burden of disease and injuries, and to attribute risk factors in Japan at a subnational, prefecture-level. We used data from GBD 2015 for 315 causes and 79 risk factors of death, disease, and injury incidence and prevalence to measure the burden of diseases and injuries in Japan and in the 47 Japanese prefectures from 1990 to 2015. We extracted data from GBD 2015 to assess mortality, causes of death, years of life lost (YLLs), years lived with disability (YLDs), disability-adjusted life-years (DALYs), life expectancy, and healthy life expectancy (HALE) in Japan and its 47 prefectures. We split extracted data by prefecture and applied GBD methods to generate estimates of burden, and attributable burden due to known risk factors. We examined the prefecture-level relationships of common health system inputs (eg, health expenditure and workforces) to the GBD outputs in 2015 to address underlying determinants of regional health variations. Life expectancy at birth in Japan increased by 4·2 years from 79·0 years (95% uncertainty interval [UI] 79·0 to 79·0) to 83·2 years (83·1 to 83·2) between 1990 and 2015. However, the gaps between prefectures with the lowest and highest life expectancies and HALE have widened, from 2·5 to 3·1 years and from 2·3 to 2·7 years, respectively, from 1990 to 2015. Although overall age-standardised death rates decreased by 29·0% (28·7 to 29·3) from 1990 to 2015, the rates of mortality decline in this period substantially varied across the prefectures, ranging from −32·4% (−34·8 to −30·0) to −22·0% (−20·4 to −20·1). During the same time period, the rate of age-standardised DALYs was reduced overall by 19·8% (17·9 to 22·0). The reduction in rates of age-standardised YLDs was very small by 3·5% (2·6 to 4·3). The pace of reduction in mortality and DALYs in many leading causes has largely levelled off since 2005. Known risk factors accounted for 34·5% (32·4 to 36·9) of DALYs; the two leading behavioural risk factors were unhealthy diets and tobacco smoking in 2015. The common health system inputs were not associated with age-standardised death and DALY rates in 2015. Japan has been successful overall in reducing mortality and disability from most major diseases. However, progress has slowed down and health variations between prefectures is growing. In view of the limited association between the prefecture-level health system inputs and health outcomes, the potential sources of regional variations, including subnational health system performance, urgently need assessment. Bill & Melinda Gates Foundation, Japan Ministry of Education, Science, Sports and Culture, Japan Ministry of Health, Labour and Welfare, AXA CR Fixed Income Fund and AXA Research Fund.

This volume is a single up-to-date source on the entire global epidemiology of diseases, injuries and risk factors with a comprehensive statement of methods and a complete presentation of results. It includes refined methods to assess data, ensure epidemiological consistency, and summarize the disease burden. Global Burden of Disease and Risk Factors examines the comparative importance of diseases, injuries, and risk factors; it incorporates a range of new data sources to develop consistent estimates of incidence, prevalence, severity and duration, and mortality for 136 major diseases and injuries. Drawing from more than 8,500 data sources that include epidemiological studies, disease registers, and notifications systems, Global Burden of Disease and Risk Factors incorporates information from more than 10,000 datasets relating to population health and mortality, representing one of the largest syntheses of global information on population health to date.