Leandro Martin Totaro Garcia’s research while affiliated with Queen's University Belfast and other places

Background The world faces increasing risk from more frequent and larger scale natural hazards, including infectious disease outbreaks (IDOs) and climate change-related extreme weather events (EWEs). These natural hazards are expected to have adverse mobility and public health impacts, with people living in cities especially vulnerable. Little is known about how transport systems can be optimally designed to make cities more resilient to these hazards. Our aim was to investigate how cities' transport systems, and their resulting mobility patterns, affect their capabilities to mitigate mobility and health impacts of future large-scale IDOs and EWEs.

Background : Despite extensive efforts to tackle the unequal levels of leisure-time physical activity (LTPA) among adults, our understanding of how these inequalities are sustained over time is minimal. Existing approaches often overlook the complex dynamic, and typically nonlinear interactions, which shape physical activity patterns. Therefore, this paper aims to capture these dynamic interactions and processes which influence an individual’s decision to practice LTPA, with a specific focus on the influence of income. Methods : The conceptual model was developed in 4 main stages: (1) initial draft development, (2) realist reviews, (3) expert consultation, and (4) finalization. Results : The conceptual model has intention as its central construct to practice LTPA, and intention is directly influenced by dynamic interrelated processes between individual’s economic, psychosocial, and perceived physical environment factors. Conclusion : From the multiple theories, evidence, and expert agreement, we are confident that our conceptual model expresses the dynamic interactions which shape an individual’s decision to practice LTPA in a context of socioeconomic inequalities. Going forward, this work will be used to conceptualize and inform the development of an agent-based model to simulate LTPA inequalities among adults and can be expanded or adapted to other uses, such as intervention development.

Background: Policy responses to the COVID-19 pandemic significantly changed city mobility patterns, including active transportation, creating a unique opportunity for global public health lessons and action. We analyzed a global natural experiment exploring city mobility patterns during the pandemic. Methods: Apple’s Mobility Trends Reports were analyzed from 296 cities during the pandemic. We synthesized global pandemic policies and recovery actions that impacted active transportation using the Shifting Streets Dataset. The public health equity of policies was investigated using PROGRESS-plus framework. Multivariate regression explored whether active transportation policies influenced city mobility patterns. Finally, a natural experiment on a global scale evaluated the effect of new active transportation policies on walking and public transit use in selected case-study cities. Findings: Overall, we observed a decline in all mobility indices (walking, driving, public transit) at the beginning of the pandemic, but the values began to increase in April 2020. Cities with lower population density had higher driving and walking indexes than cities with higher population density, while cities with higher population density had higher public transit indexes. Cities with higher COVID-19 infection rates had higher driving and walking indexes than cities with lower COVID-19 infection rates, while cities in Q2 COVID-19 infection rates had higher public transit indexes than other cities. Policies were implemented in 230 cities within 33 countries (including 19 high-income, 11 middle-income, and 3 low-income). For the global experiment (including 36 cities), setting the intervention point in mid-April 2020, the absolute value of the walking index was significantly higher after the policy intervention (Coef. = 23.105; SE = 3.253), and the increase of the walking index after the policy intervention was higher than the decrease of the walking index before the policy intervention (Coef. = 22.378; SE = 1.774). Interpretation: Our results emphasize the importance of maintaining and expanding policies implemented to mitigate the COVID-19 pandemic, which changes city mobility patterns, including increased active transportation. Improving infrastructure to promote safe walking, cycling, and access to public transit use should be prioritized in low and middle-income countries for equitable future-proofing of cities from global pandemics.

Inequalities in physical activity are well documented, especially between socioeconomic groups. However, progress on reducing these inequalities is proving challenging. In this commentary, we argue that a complex system perspective is needed, specifically to reorient our thinking of inequalities in physical activity to be emergent features of complex systems. Operationalising this perspective involves acknowledging the multiple dynamic and non-linear interactions which take place between system parts and, over time aggregate to become macro patterns such as physical activity inequalities. We argue that this framing will enhance our understanding of the emergence of inequalities in physical activity and, therefore, provide interventions better suited to the subgroups of the population they are designed to help.

Background : Despite the existence of physical activity policies across many countries, insufficient physical activity remains a major global public health problem. Physical inactivity is an emergent feature of complex systems; it results from a wide range of factors at multiple levels that interact to influence behavior. Traditional approaches to public policy often fail within complex systems, largely due to unpredictability in how the system will respond. Adaptive policies, which are designed to allow for uncertainty about future system behavior and to change over time, may offer a promising solution. In this paper, we introduce the concept of adaptive policies and illustrate how this innovative approach to policy making may be beneficial for reducing physical inactivity. Design : Drawing on existing literature and guiding principles for policy making, we provide 3 examples to illustrate how the concept of adaptive policies can be applied to address physical inactivity. Discussion : The examples illustrate how changes to the way policies and interventions are developed, implemented, and evaluated could help to overcome some of the limitations in existing practices. A key challenge will be engaging policymakers to take a broader perspective of the physical activity system, develop policies that are designed to be adaptable across a range of different future scenarios, and embrace uncertainty and long-term adaptability. Conclusion : Adaptive policies may support decision makers globally to achieve the widespread and sustained changes necessary to increase population levels of physical activity.

The intricate relationship between food systems and health outcomes, known as the food-nutrition-health nexus, intersects with environmental concerns. However, there’s still a literature gap in evaluating food systems alongside the global syndemic using the complex systems theory, especially concerning vulnerable populations like children. This research aimed to design a system dynamics model to advance a theoretical understanding of the connections between food systems and the global syndemic, particularly focusing on their impacts on children under five years of age. The framework was developed through a literature review and authors’ insights into the relationships between the food, health, and environmental components of the global syndemic among children. The conceptual model presented 17 factors, with 26 connections and 6 feedback loops, categorized into the following 5 groups: environmental, economic, school-related, family-related, and child-related. It delineated and elucidated mechanisms among the components of the global syndemic encompassing being overweight, suffering from undernutrition, and climate change. The findings unveiled potential interactions within food systems and health outcomes. Furthermore, the model integrated elements of the socio-ecological model by incorporating an external layer representing the environment and its natural resources. Consequently, the development of public policies and interventions should encompass environmental considerations to effectively tackle the complex challenges posed by the global syndemic.

Resumo Este estudo teve como objetivo descrever um inquérito quantitativo realizado com lideranças para investigar ações efetivas, viáveis e que podem ser testadas em modelos computacionais para informar políticas de promoção da mobilidade ativa, tendo como base a cidade de São Paulo, Brasil. Em 2022, foi realizado um inquérito online no contexto da pesquisa de Atividade Física e Ambiente do Inquérito de Saúde de São Paulo, acompanhada por representantes de organizações não governamentais, gestores públicos e de entidades privadas. Foi elaborado questionário com três perguntas com 13 alternativas de respostas sobre ações para promoção da caminhada ou uso de bicicleta. As lideranças deveriam selecionar até três alternativas a partir de seu potencial em termos de (1) efetividade; (2) viabilidade ou facilidade de implementação; e (3) desejo de realizar testes em modelos computacionais para informar políticas. O inquérito foi respondido por 18 lideranças de 16 instituições, sendo 13 (72%) mulheres e 12 (67%) representantes do terceiro setor, cuja média de idade era 48 anos, todos com nível superior de escolaridade. A redução da velocidade dos veículos motorizados foi a opção mais citada nas três questões. Outras ações citadas referem-se ao controle de circulação de veículos em regiões centrais, à segurança de pedestres, à diminuição das distâncias entre residências e locais de emprego, às campanhas educativas e à ampliação e melhoria de estruturas como ciclovias e calçadas. Os resultados são relevantes para apoiar a tomada de decisões baseadas em evidências na gestão pública e oferecer subsídios para a elaboração de modelos computacionais com vistas à promoção da mobilidade ativa.

Objective: Associations between place and population health are of interest to researchers and policymakers. The objective of this paper is to explore, summarise and compare content across contemporary Australian geo-referenced population health survey data sets. Methods: A search for recent (2015 or later) population health surveys from within Australia containing geographic information from participants was conducted. Survey response frames were analysed and categorised based on demographic, risk factor and disease-related characteristics. Analysis using interactive Sankey diagrams shows the extent of content overlap and differences between population health surveys in Australia. Results: Thirteen Australian geo-referenced population health survey data sets were identified. Information captured across surveys was inconsistent as was the spatial granularity of respondent information. Health and demographic features most frequently captured were symptoms, signs and clinical findings from the International Statistical Classification of Diseases and Related Health Problems version 11, employment, housing, income, self-rated health and risk factors, including alcohol consumption, diet, medical treatments, physical activity and weight-related questions. Sankey diagrams were deployed online for use by public health researchers. Conclusions: Identifying the relationship between place and health in Australia is made more difficult by inconsistencies in information collected across surveys deployed in different regions in Australia. Implications for Public Health: Public health research investigating place and health involves a vast and inconsistent patchwork of information within and across states, which may impact broad-scale research questions. The tools developed here assist public health researchers to identify surveys suitable for their research queries related to place and health.