Background: Population health is influenced by interactions between environmental determinants, which are captured by dimensions and indicators. This study aims to systematically review key environmental determinants and respective dimensions and indicators, relevant to evaluate population health in urban settings, and to understand their potential implications into policies. Methods: A search of literature published between 2008 and 2018 was conducted in PubMed, Web of Science, Scopus and SciELO Portugal databases, on studies with evidence on association between an environmental determinant and a health outcome in urban contexts. Health determinants, dimensions and indicators researched in the selected studies were synthetized, and associations analyzed. An independent assessment of quality of the studies was performed. Key conclusions and policy recommendations were extracted to build a framework to analyze environment related population health and policies in urban settings. Results: Ninety four studies of varied methodological approaches and quality met the inclusion criteria. The review identified positive associations between all environmental determinants -socioeconomic, built environment, natural environment, healthcare, behaviors, and health outcomes - overall mortality and morbidity, in urban settings. Improvements in income, education, air quality, occupation status, mobility and smoking habits indicators have positive impact in overall mortality and chronic diseases morbidity indicators. Initiatives to improve population health in which policymakers can be more evidence-informed include socioeconomic, natural environment and built environment determinants. Conclusions: There is scope and need to further explore which environmental determinants and dimensions most contribute to population health to create a series of robust evidence-based measures to better inform urban planning policies.

Background Multi-criteria decision analysis (MCDA) concepts, models and tools have been used increasingly in health technology assessment (HTA), with several studies pointing out practical and theoretical issues related to its use. This study provides a critical review of published studies on MCDA in the context of HTA by assessing their methodological quality and summarising methodological challenges. Methods A systematic review was conducted to identify studies discussing, developing or reviewing the use of MCDA in HTA using aggregation approaches. Studies were classified according to publication time and type, country of study, technology type and study type. The PROACTIVE-S approach was constructed and used to analyse methodological quality. Challenges and limitations reported in eligible studies were collected and summarised; this was followed by a critical discussion on research requirements to address the identified challenges. Results 129 journal articles were eligible for review, 56% of which were published in 2015–2017; 42% focused on pharmaceuticals; 36, 26 and 18% reported model applications, issues regarding MCDA implementation analyses, and proposing frameworks, respectively. Poor compliance with good methodological practice (< 25% complying studies) was found regarding behavioural analyses, discussion of model assumptions and uncertainties, modelling of value functions, and dealing with judgment inconsistencies. The five most reported challenges related to evidence and data synthesis; value system differences and participant selection issues; participant difficulties; methodological complexity and resource balance; and criteria and attributes modelling. A critical discussion on ways to address these challenges ensues. Discussion Results highlight the need for advancement in robust methodologies, procedures and tools to improve methodological quality of MCDA in HTA studies. Research pathways include developing new model features, good practice guidelines, technologies to enable participation and behavioural research.

Indicators are essential instruments for monitoring and evaluating population health. The selection of a multidimensional set of indicators should not only reflect the scientific evidence on health outcomes and health determinants, but also the views of health experts and stakeholders. The aim of this study is to describe the Delphi selection process designed to promote agreement on indicators considered relevant to evaluate population health at the European regional level. Indicators were selected in a Delphi survey conducted using a web-platform designed to implement and monitor participatory processes. It involved a panel of 51 experts and 30 stakeholders from different areas of knowledge and geographies. In three consecutive rounds the panel indicated their level of agreement or disagreement with indicator’s relevance for evaluating population health in Europe. Inferential statistics were applied to draw conclusions on observed level of agreement (Scott’s Pi interrater reliability coefficient) and opinion change (McNemar Chi-square test). Multivariate analysis of variance was conducted to check if the field of expertise influenced the panellist responses (Wilk’s Lambda test). The panel participated extensively in the study (overall response rate: 80%). Eighty indicators reached group agreement for selection in the areas of: economic and social environment (12); demographic change (5); lifestyle and health behaviours (8); physical environment (6); built environment (12); healthcare services (11) and health outcomes (26). Higher convergence of group opinion towards agreement on the relevance of indicators was seen for lifestyle and health behaviours, healthcare services, and health outcomes. The panellists’ field of expertise influenced responses: statistically significant differences were found for economic and social environment (p < 0.05 in round 1 and 2), physical environment (p < 0.01 in round 1) and health outcomes (p < 0.01 in round 3). The high levels of participation observed in this study, by involving experts and stakeholders and ascertaining their views, underpinned the added value of using a transparent Web-Delphi process to promote agreement on what indicators are relevant to appraise population health.