Socioecological determinants of child oral health-A scoping review

OBJECTIVES

Child oral health is a result of interactions between multilevel influences within a complex system. Understanding those interactions informs conceptualizing a socioecological framework of important influences on oral health. This paper aimed to present a scoping review on the determinants of dental caries and their interactions in childhood and adolescence.

METHODS

The two review questions were as follows: Which factors are determinants of child dental caries? and, How do determinants interact within and across socioecological levels? The three main electronic databases for biomedical records, PubMed, Web of Science and Scopus were searched, followed by reference check. The search and screening/selection procedures followed an a priori strategy and inclusion/exclusion criteria were specified in advance. The main components of the strategy were participants, concept and context. Following the final selection, eligible studies were assessed with quality appraisal tools for the risk of methodologic biases. Determinants reported in the included studies were then assigned to the micro-, meso-, exo- or macro-systems levels in a socioecological framework. Interactions between determinants were also identified and reported.

RESULTS

A total of 100 studies were included after removal of duplicates, screening on the title/abstracts and full-text assessment among 3313 records initially identified. A higher number of studies included were cross-sectional studies published in recent years. The majority of determinants found to influence child dental health were assigned to microsystem level within the framework. However, determinants were found at all levels and interactions were reported within and between socioecological levels. Determinants identified in the scoping review represent factors at different socioecological levels that influence child oral health.

CONCLUSION

Application of a socioecological model through a complex systems approach should lead to valid and robust progress towards practical solutions for better child oral health globally.

A Transdisciplinary Framework to Unlock the Potential Benefits of Green Spaces for Urban Communities Under Changing Contexts

New urban models increasingly seek to create more sustainable, livable, and healthier cities by reinvigorating green space. In this article, we highlight and briefly review several main but disconnected areas of study in which the factors that frame human-environment interactions and therefore also influence the potential well-being outcomes of those interactions are studied. We then use the intersection of affordance theory and socio-institutional programming to provide a conceptual framework that ties together these spheres of research, and we discuss some critical keys for enabling different positive green space experiences. Urban communities are not homogeneous, and accounting for the intersection between individual differences and landscape programming opens up more diverse pathways for affording positive human-environment interactions and different well-being outcomes.

Grand challenges in biodiversity-ecosystem functioning research in the era of science-policy platforms require explicit consideration of feedbacks

Feedbacks are an essential feature of resilient socio-economic systems, yet the feedbacks between biodiversity, ecosystem services and human wellbeing are not fully accounted for in global policy efforts that consider future scenarios for human activities and their consequences for nature. Failure to integrate feedbacks in our knowledge frameworks exacerbates uncertainty in future projections and potentially prevents us from realizing the full benefits of actions we can take to enhance sustainability. We identify six scientific research challenges that, if addressed, could allow future policy, conservation and monitoring efforts to quantitatively account for ecosystem and societal consequences of biodiversity change. Placing feedbacks prominently in our frameworks would lead to (i) coordinated observation of biodiversity change, ecosystem functions and human actions, (ii) joint experiment and observation programmes, (iii) more effective use of emerging technologies in biodiversity science and policy, and (iv) a more inclusive and integrated global community of biodiversity observers. To meet these challenges, we outline a five-point action plan for collaboration and connection among scientists and policymakers that emphasizes diversity, inclusion and open access. Efforts to protect biodiversity require the best possible scientific understanding of human activities, biodiversity trends, ecosystem functions and—critically—the feedbacks among them.

Linking human and ecological components to understand human-wildlife conflicts across landscapes and species

Human-wildlife conflicts (HWC) are complex conservation challenges that impair both wildlife populations and human livelihood. Research on HWC, however, has traditionally approached ecological and human components separately, hampering a broader understanding of connections between ecological drivers and human dimensions of conflicts. We developed a model that integrates ecological and human components of HWC to investigate how the amount of remaining native forest (forest cover, a key ecological variable known to influence species occurrence and abundance) affects human experiences with wildlife (contact with species and attacks on livestock) and how such experiences influence tolerance via beliefs, emotions, and attitudes. We tested the model with piecewise structural equation modeling and data on human interactions with 3 mammals with different rarity and body size: opossum (Didelphis aurita), crab-eating fox (Cerdocyon thous), and puma (Puma concolor). Data were obtained by interviewing 114 landowners across 13 Atlantic Forest landscapes (10-50% forest cover). Forest cover was associated with high chance of attacks on livestock, and thus with low tolerance, only in the case of the puma. Effects of distinct experiences with wildlife on beliefs and emotions varied across species. Beliefs and emotions toward wildlife influenced tolerance toward all species, but negative emotions affected tolerance toward only with the puma. Conflicts with large carnivores, such as pumas, can then be understood as disservices provided by forests, indicating the relevance of framing HWC more broadly to consider trade-offs with ecosystems services. For some species, positive experiences with wildlife may counteract the negative effects of attacks on livestock in shaping tolerance. Models such as ours-that link ecological and human dimensions-can help identify more effective leverage points to improve HWC mitigation.

Design trade-offs in rights-based management of small-scale fisheries

Small-scale fisheries collectively have a large ecological footprint and are key sources of food security, especially in developing countries. Many of the data-intensive approaches to fishery management are infeasible in these fisheries, but a strategy that has emerged to overcome these challenges is the establishment of territorial user rights for fisheries (TURFs). In this approach, exclusive fishing zones are established for groups of stakeholders, which eliminates the race to fish with other groups. A key challenge, however, is setting the size of TURFs-too large and the number of stakeholders sharing them impedes collective action, and too small and the movement of target fish species in and out of the TURFs effectively removes the community's exclusive access. We assessed the size of 137 TURFs from across the globe relative to this design challenge by applying theoretical models that predict their performance. We estimated that roughly two-thirds of these TURFs were sized ideally to overcome the challenges posed by resource movement and fisher group size. However, for most of the remaining TURFs, all possible sizes were either too small to overcome the resource-movement challenge or too large to overcome the collective action challenge. Our results suggest these fisheries, which target mobile species in densely populated regions, may need additional interventions to be successful.

Regional fire scenarios in Spain: Linking landscape dynamics and fire regime for wildfire risk management

Fire scenarios are multiscale land-type planning units for a fire regime with different applications at national, regional, and local scales. The main aim of this research is to implement a methodology integrating landscape dynamics and wildfire risk from a context-specific approach, to identify current fire scenarios at a regional scale in the Spanish Central Mountain Range. These homogeneous areas are linked to different stages of a territorial dynamics model called wildfire generations and related to land use diversity and land management trends. A place-based methodology has been developed to characterize fire scenarios using Geographic Information Systems and statistical analysis, resulting in analytical and diagnostic mapping that can be used as a decision support tool for spatial planning and wildfire risk management. Its implementation has led to the delimitation of 91 discrete geographic units in the Central Mountain Range, classified according to wildfire generations and land use-land cover criteria. In conclusion, the fire scenarios concept is a potential approach to manage uncertainty by moving from the operational level of fire suppression to the strategic level of integrated fire management.

Socioecologically informed use of remote sensing data to predict rural household poverty

Tracking the progress of the Sustainable Development Goals (SDGs) and targeting interventions requires frequent, up-to-date data on social, economic, and ecosystem conditions. Monitoring socioeconomic targets using household survey data would require census enumeration combined with annual sample surveys on consumption and socioeconomic trends. Such surveys could cost up to $253 billion globally during the lifetime of the SDGs, almost double the global development assistance budget for 2013. We examine the role that satellite data could have in monitoring progress toward reducing poverty in rural areas by asking two questions: (i) Can household wealth be predicted from satellite data? (ii) Can a socioecologically informed multilevel treatment of the satellite data increase the ability to explain variance in household wealth? We found that satellite data explained up to 62% of the variation in household level wealth in a rural area of western Kenya when using a multilevel approach. This was a 10% increase compared with previously used single-level methods, which do not consider details of spatial landscape use. The size of buildings within a family compound (homestead), amount of bare agricultural land surrounding a homestead, amount of bare ground inside the homestead, and the length of growing season were important predictor variables. Our results show that a multilevel approach linking satellite and household data allows improved mapping of homestead characteristics, local land uses, and agricultural productivity, illustrating that satellite data can support the data revolution required for monitoring SDGs, especially those related to poverty and leaving no one behind.

Critical dynamics in population vaccinating behavior

Complex adaptive systems exhibit characteristic dynamics near tipping points such as critical slowing down (declining resilience to perturbations). We studied Twitter and Google search data about measles from California and the United States before and after the 2014–2015 Disneyland, California measles outbreak. We find critical slowing down starting a few years before the outbreak. However, population response to the outbreak causes resilience to increase afterward. A mathematical model of measles transmission and population vaccine sentiment predicts the same patterns. Crucially, critical slowing down begins long before a system actually reaches a tipping point. Thus, it may be possible to develop analytical tools to detect populations at heightened risk of a future episode of widespread vaccine refusal.

Vaccine refusal can lead to renewed outbreaks of previously eliminated diseases and even delay global eradication. Vaccinating decisions exemplify a complex, coupled system where vaccinating behavior and disease dynamics influence one another. Such systems often exhibit critical phenomena—special dynamics close to a tipping point leading to a new dynamical regime. For instance, critical slowing down (declining rate of recovery from small perturbations) may emerge as a tipping point is approached. Here, we collected and geocoded tweets about measles–mumps–rubella vaccine and classified their sentiment using machine-learning algorithms. We also extracted data on measles-related Google searches. We find critical slowing down in the data at the level of California and the United States in the years before and after the 2014–2015 Disneyland, California measles outbreak. Critical slowing down starts growing appreciably several years before the Disneyland outbreak as vaccine uptake declines and the population approaches the tipping point. However, due to the adaptive nature of coupled behavior–disease systems, the population responds to the outbreak by moving away from the tipping point, causing “critical speeding up” whereby resilience to perturbations increases. A mathematical model of measles transmission and vaccine sentiment predicts the same qualitative patterns in the neighborhood of a tipping point to greatly reduced vaccine uptake and large epidemics. These results support the hypothesis that population vaccinating behavior near the disease elimination threshold is a critical phenomenon. Developing new analytical tools to detect these patterns in digital social data might help us identify populations at heightened risk of widespread vaccine refusal.

A typology of time-scale mismatches and behavioral interventions to diagnose and solve conservation problems

Ecological systems often operate on time scales significantly longer or shorter than the time scales typical of human decision making, which causes substantial difficulty for conservation and management in socioecological systems. For example, invasive species may move faster than humans can diagnose problems and initiate solutions, and climate systems may exhibit long-term inertia and short-term fluctuations that obscure learning about the efficacy of management efforts in many ecological systems. We adopted a management-decision framework that distinguishes decision makers within public institutions from individual actors within the social system, calls attention to the ways socioecological systems respond to decision makers' actions, and notes institutional learning that accrues from observing these responses. We used this framework, along with insights from bedeviling conservation problems, to create a typology that identifies problematic time-scale mismatches occurring between individual decision makers in public institutions and between individual actors in the social or ecological system. We also considered solutions that involve modifying human perception and behavior at the individual level as a means of resolving these problematic mismatches. The potential solutions are derived from the behavioral economics and psychology literature on temporal challenges in decision making, such as the human tendency to discount future outcomes at irrationally high rates. These solutions range from framing environmental decisions to enhance the salience of long-term consequences, to using structured decision processes that make time scales of actions and consequences more explicit, to structural solutions aimed at altering the consequences of short-sighted behavior to make it less appealing. Additional application of these tools and long-term evaluation measures that assess not just behavioral changes but also associated changes in ecological systems are needed.