The globally distributed health impacts of environmental degradation and widening population inequalities require a fundamental shift in understandings of healthy urbanism – including policies and decisions that shape neighbourhood and building design. The built environment tends to disadvantage or exclude women, children, the elderly, disabled, poor and other groups, starting from design and planning stages through to occupation, and this results in avoidable health impacts. Although these concepts are not new, they are rapidly emerging as built environment research and practice priorities without clear understanding of the interconnected aims of healthy environments that are sustainable, equitable and inclusive. This article promotes a new framework – Towards Healthy uRbanism: InclusiVe Equitable Sustainable (THRIVES) – that extends previous conceptualisations and reorients focus towards the existential threat of environmental breakdown and the social injustice created through inequitable and exclusive urban governance and design processes and outcomes. The Framework was developed through synthesising knowledge from research and practice, and by testing this new conceptualisation in a participatory workshop. Ongoing research is exploring implementation of the Framework in practice. If widely adopted, this Framework may contribute towards achieving the goals of sustainable development through a focus on increasing human health and wellbeing in urban development.

Urban health indicator (UHI) tools provide evidence about the health impacts of the physical urban environment which can be used in built environment policy and decision-making. Where UHI tools provide data at the neighborhood (and lower) scale they can provide valuable information about health inequalities and environmental deprivation. This review performs a census of UHI tools and explores their nature and characteristics (including how they represent, simplify or address complex systems) to increase understanding of their potential use by municipal built environment policy and decision-makers. We searched seven bibliographic databases, four key journals and six practitioner websites and conducted Google searches between January 27, 2016 and February 24, 2016 for UHI tools. We extracted data from primary studies and online indicator systems. We included 198 documents which identified 145 UHI tools comprising 8006 indicators, from which we developed a taxonomy. Our taxonomy classifies the significant diversity of UHI tools with respect to topic, spatial scale, format, scope and purpose. The proportions of UHI tools which measure data at the neighborhood and lower scale, and present data via interactive maps, have both increased over time. This is particularly relevant to built environment policy and decision-makers, reflects growing analytical capability and offers the potential for improved understanding of the complexity of influences on urban health (an aspect noted as a particular challenge by some indicator producers). The relation between urban health indicators and health impacts attributable to modifiable environmental characteristics is often indirect. Furthermore, the use of UHI tools in policy and decision-making appears to be limited, thus raising questions about the continued development of such tools by multiple organisations duplicating scarce resources. Further research is needed to understand the requirements of built environment policy and decision-makers, public health professionals and local communities regarding the form and presentation of indicators which support their varied objectives.

Public health practitioners produce urban health indicator (UHI) tools to inform built environment policy and decision-making, among other objectives. Indicator producers perceive UHI tools as an easily understandable form of evidence about the urban environment impact on health for policy-makers’ consumption. However, indicator producers often conceptualise policy-making as a rational and linear process, therefore underestimating the complex and contested nature of developing and implementing policy. This study investigates the health-promotion value of UHI tools in the complex urban planning policy and decision-making context. A thematic analysis was conducted following semi-structured interviews with 22 indicator producers and users in San Francisco, Melbourne and Sydney. The analysis was informed by collaborative rationality and systems theories and the results were used to develop causal loop diagrams (CLDs) of producers and users’ mental models. The preliminary CLDs were tested and improved through a participatory modelling workshop (six participants). A high-level CLD depicts users and producers’ shared mental model in which indicator development and use are embedded in policy development and application processes. In the cases analysed, creating and using UHI tools increased inter-sectoral relationships, which supported actors to better understand each other’s opportunities and constraints. These relationships spurred new advocates for health in diverse organisations, supporting health-in-all-policies and whole-of-society approaches. Constraints to health-promoting policy and implementation (such as those which are legal, political and economic in nature), were overcome through community involvement in UHI tools and advocacy effectiveness. A number of factors reduced the perceived relevance and authority of UHI tools, including: a high number of available indicators, lack of neighbourhood scale data and poor-quality data. In summary, UHI tools were a form of evidence that influenced local urban planning policy and decision-making when they were embedded in policy processes, networks and institutions. In contrast to the dominant policy impact model in the indicator literature, such evidence did not typically influence policy as an exogenous entity. Indicators had impact when they were embedded in local institutions and well-resourced over time, resulting in trusted relationships and collaborations among indicator producers and users. Further research is needed to explore other governance contexts and how UHI tools affect the power of different actors, particularly for under-represented communities.

Transdisciplinary research approaches are being applied to today’s complex health problems, including the climate crisis and widening inequalities. Diverse forms of disciplinary and experiential knowledge are required to understand these challenges and develop workable solutions. We aimed to create an updated model reflective of the strengths and challenges of current transdisciplinary health research that can be a guide for future studies. We searched Medline using terms related to transdisciplinary, health and research. We coded data deductively and inductively using thematic analysis to develop a preliminary model of transdisciplinary research. The model was tested and improved through: (i) a workshop with 27 participants at an international conference in Xiamen, China and (ii) online questionnaire feedback from included study authors. Our revised model recommends the following approach: (i) co-learning, an ongoing phase that recognizes the distributed nature of knowledge generation and learning across partners; (ii) (pre-)development, activities that occur before and during project initiation to establish a shared mission and ways of working; (iii) reflection and refinement to evaluate and improve processes and results, responding to emergent information and priorities as an ongoing phase; (iv) conceptualization to develop goals and the study approach by combining diverse knowledge; (v) investigation to conduct the research; (vi) implementation to use new knowledge to solve societal problems. The model includes linear and cyclical processes that may cycle back to project development. Our new model will support transdisciplinary research teams and their partners by detailing the necessary ingredients to conduct such research and achieve health impact.

There is a growing awareness among city leaders and policy-makers of the impact of the urban environment on health outcomes and inequalities. Increasingly, practitioners in built environment city departments, such as housing, planning, transport and regeneration, seek new tools and guidance to understand how their respective policies and decisions can support the creation of healthier cities. This paper presents the development of a global index to help city leaders and practitioners understand their role in delivering health outcomes through urban environment policies and programmes. The Building Research Establishment’s international Healthy Cities Index (BRE HCI) contains 10 environment categories and 58 indicators, supported by a causal pathways framework. This was achieved through an iterative process including: stakeholder engagement, evaluating research evidence, selecting indicators and identifying data sources. We tested the index and causal pathways approach on two case study cities: Dubai and London. We found that they contributed to: raising awareness of the links between the environment and health; identifying shared responsibilities and the need to work across departmental silos; and uncovering the competing demands faced by some departments (and private sector stakeholders) as they seek to deliver health promoting environments alongside other objectives.

Background: Household overcrowding is associated with increased risk of infectious diseases across contexts and countries. Limited data exist linking household overcrowding and risk of COVID-19. We used data collected from the Virus Watch cohort to examine the association between overcrowded households and SARS-CoV-2. Methods: The Virus Watch study is a household community cohort of acute respiratory infections in England and Wales. We calculated overcrowding using the measure of persons per room for each household. We considered two primary outcomes: PCR-confirmed positive SARS-CoV-2 antigen tests and laboratory-confirmed SARS-CoV-2 antibodies. We used mixed-effects logistic regression models that accounted for household structure to estimate the association between household overcrowding and SARS-CoV-2 infection. Results: 26,367 participants were included in our analyses. The proportion of participants with a positive SARS-CoV-2 PCR result was highest in the overcrowded group (9.0%; 99/1,100) and lowest in the under-occupied group (4.2%; 980/23,196). In a mixed-effects logistic regression model, we found strong evidence of an increased odds of a positive PCR SARS-CoV-2 antigen result (odds ratio 2.45; 95% CI:1.43–4.19; p-value=0.001) and increased odds of a positive SARS-CoV-2 antibody result in individuals living in overcrowded houses (3.32; 95% CI:1.54–7.15; p-value<0.001) compared with people living in under-occupied houses. Conclusion: Public health interventions to prevent and stop the spread of SARS-CoV-2 should consider the risk of infection for people living in overcrowded households and pay greater attention to reducing household transmission.