Engineered Living Materials, or ELMs, integrate living cells within engineered scaffolds to create adaptive and responsive functions. Living artefacts extend this approach by incorporating living organisms as active participants in designed objects, where biological activity contributes to ongoing responsiveness, interaction, and new forms of human–living system relationships. Both approaches have expanded the role of biology in design, positioning living systems as functional and tuneable components. However, current applications remain largely confined to discrete objects or material components, meaning microbial life in design is often spatially bounded and considered at short temporal scales. This limits the ability to engage with microbial systems as distributed ecological networks across built environments.

The archibiome concept addresses this gap by defining the subset of the built-environment microbiome that is intentionally shaped through architectural and material interventions. It includes both engineered microorganisms introduced through ELMs and native microbial communities whose recruitment, selection, and interactions are modulated through design strategies. Conceptually, the archibiome treats the built environment as a multiscale, feedback-controlled system integrating microbial community dynamics, engineered materials, and environmental conditions. Microbial processes are coupled to architectural parameters such as material composition, spatial configuration, moisture, light, and temperature through feedback loops in which system outputs influence future system states. This enables the prediction and regulation of system-level functions such as carbon sequestration, pollutant degradation, oxygen production, and self-regeneration.

Existing terms like building microbiomes, indoor microbiomes, and urban microbiome are primarily descriptive, characterizing microbial assemblages as emergent outcomes of environmental and design conditions without distinguishing whether or how these communities are intentionally shaped. The archibiome differs by framing microbial communities as integral, designable ecosystems distributed within architectural and infrastructural systems. Rather than focusing on isolated artefacts, the framework addresses how microbial processes are distributed and coordinated across spatial, temporal, and infrastructural scales, including their interactions with environmental conditions and human occupants. ELMs act as enabling technologies through which microbial functions can be engineered, monitored, and controlled, while living artefacts represent localized implementations within a broader ecological system.

Depending on their design, ELMs can perform biocatalytic functions such as bioremediation and carbon sequestration, bioreceptive functions such as protection and self-healing, and responsive functions such as sensing and signalling. The intrinsic capacity of ELMs for self-regeneration and self-healing can substantially reduce maintenance requirements and material replacement over time, aligning with circular bioeconomy principles by lowering resource consumption and enhancing the environmental sustainability of building systems. The archibiome is not only defined by intentional design but by the explicit integration of microbial dynamics with architectural control parameters, focusing on how microbial communities are regulated through spatially distributed gradients and feedback mechanisms including nutrient fluctuations, moisture regimes, material properties, and environmental exposure.

The importance of this framework is profound, particularly as modern humans spend up to 90 percent of their lives indoors. This prolonged exposure means indoor microbial communities, being an integral part of the exposome, play a critical role in shaping human health and wellbeing. Indoor air quality, exposed surfaces, and building materials shape the microbial landscape we interact with daily. While increasing evidence suggests associations between indoor microbial communities and human health, these relationships remain largely correlational, and further work is required to establish causal mechanisms and evidence-based design strategies. Designing indoor spaces with microbial ecosystems in mind therefore represents a promising but still emerging approach with direct implications for sustainability, as microbial communities contribute to carbon and nutrient cycling, pollutant degradation, and environmental buffering.

Adopting an archibiome perspective also raises challenges beyond design and material integration. Engineering microbial ecosystems at the scale of buildings requires careful attention to long-term dynamics, system stability, and unintended ecological consequences. It intersects with regulatory frameworks that are still evolving, particularly for products that intentionally introduce living microorganisms into built environments. Each ELM product is inherently unique, containing different organisms and having different functions and intended uses, meaning one-size-fits-all regulatory pathways are insufficient. Regulatory uncertainty can slow the translation of research into practice, as extensive testing is required to demonstrate safety, efficacy, and ecological compatibility. In both the European Union and the United States, agencies enforce strict biosafety regulations that consider the potential spread of microorganisms beyond the targeted environment. If genetically modified microorganisms are involved, additional requirements address their origin, genetic modifications, and potential for horizontal gene transfer.

Public perception is another critical factor. Concerns include uncontrolled microbial growth, allergenic responses, and survival of pathogenic organisms in sensitive environments such as hospitals or schools. These issues highlight the need for transparent communication and robust safety classification systems such as Qualified Presumption of Safety, Risk Group classifications, and FDA GRAS frameworks. Ensuring long-term stability and safety of ELMs requires both physical and biological containment strategies. Hydrogels, thermogels, and synthetic or natural polymers can physically constrain microbial growth, while genetic and metabolic engineering of microorganisms limits their survival, proliferation, or gene exchange outside intended conditions through approaches such as auxotrophy, kill-switches, or dependency on specific substrates. These approaches demonstrate the feasibility of creating living materials that are controllable, safe, and predictable.

From a systems biology perspective, the archibiome can be formalized as a coupled multiscale dynamical system linking intracellular regulatory networks, interspecies interactions, and environmentally mediated boundary conditions. At the microscale, stochastic or constraint-based metabolic models can describe microbial responses to environmental stimuli including nutrient availability, stress, and signalling dynamics. At the mesoscale, large hierarchical and consumer–resource models can capture competitive and cooperative dynamics governing community assembly and functional stability. At the macroscale, Building Information Modelling or computational fluid dynamics can represent processes and environmental heterogeneity in the built environment. These modelling layers can be integrated into a unified hybrid framework in which microbial dynamics are coupled to time-varying environmental fields defined by architectural parameters such as airflow, humidity gradients, surface chemistry, and material porosity, enabling the formulation of the built environment as a feedback-controlled ecological system.

Emerging research projects illustrate how the archibiome concept can be operationalized in practice. The ARCHI-SKIN project develops living coating systems based on the biofilm-forming fungus Aureobasidium pullulans, designed to protect building materials through self-regenerating and metabolically active layers. In this context, microbial performance is not only determined by species selection but by the interaction between substrate properties, nutrient availability, and environmental conditions. Complementary to this approach, the REMEDY project explores the integration of designed microbial consortia as living inks for architectural surfaces, combining functions such as carbon sequestration, pollutant remediation, and microbial balance with spatial patterning and digital fabrication strategies. For living active inks developed for architectural surfaces targeting carbon sequestration up to 15 kg CO2 per 10 square meters per year, oxygen production via photosynthesis up to 10 kg O2 per 10 square meters per year, self-regeneration with healing distance up to 2 millimeters, and bioremediation up to 140 kg VOCs per cubic meter of air per year, it can be hypothesized that spatial variation in environmental exposure such as light intensity, moisture availability, temperature, and airflow regimes will differentially modulate microbial metabolic activity and community composition across building surfaces. This hypothesis can be operationalized by predictive models of microbial growth and metabolite exchange with computational fluid dynamics simulations of airflow, light distribution, and humidity gradients, enabling prediction of spatially resolved performance metrics. Empirical validation can then be achieved through meta-omics data combined with in situ measurements of CO2 uptake, O2 production, and VOC degradation under both controlled and natural weathering conditions. Such an approach directly links design variables like façade orientation, material porosity, and environmental buffering capacity with quantifiable ecological and functional outcomes, supporting iterative refinement of both models and archibiome-informed design strategies. Ultimately, the archibiome does not diverge from the ELM field but extends its conceptual and operational boundaries, highlighting how advances in ELMs, synthetic biology, and systems biology can converge to support the development of adaptive, multifunctional built environments and marking a shift from descriptive to predictive and engineering-driven approaches to living systems in architecture.

Subject of Research: Microbial Ecology and Architecture

Article Title: The archibiome: extending engineered living materials to multiscale built environments

Article References: Sandak, A., Pajerski, W., Gubenšek, A., Butina Ogorelec, K., & Černoša, A. (2026). The archibiome: extending engineered living materials to multiscale built environments. Frontiers in Systems Biology, 6, Article 1943876. https://doi.org/10.3389/fsysb.2026.1943876

Image Credits: AI Generated

DOI: 10.3389/fsysb.2026.1943876

Keywords: archibiome, engineered living materials, built environment, microbiome, probiotic design, regenerative architecture, synthetic biology, systems biology, extending, engineered, living, materials

The numbers tell a stark story. Perceived availability of sports facilities or adequate spaces near the home was 92.1 percent among adults with disabilities and 91.4 percent among those without, a difference so small it vanished statistically (crude prevalence ratio 1.01; 95 percent CI 0.99 to 1.03; p = 0.478). But when the researchers asked who actually used those available spaces, the picture inverted. Only 29.9 percent of adults with disabilities who had spaces nearby reported using them, compared with 42.7 percent of adults without disabilities. That translates into a 22 percent higher prevalence of non-use among people with disabilities, a gap that persisted even after the researchers adjusted for sex, age group and socioeconomic status.

The study, published in Frontiers in Sports and Active Living, is the first to separate perceived availability from actual use along the full access chain in a national surveillance instrument, and it does so with unusual methodological care. The team classified disability into six mutually exclusive categories: sensory only, physical only, cognitive only, multiple types, other only, and none. They then used weighted Poisson regression with robust variance to estimate prevalence ratios, adjusting for confounders selected a priori through a directed acyclic graph rather than by statistical fishing. Because the public database provided survey weights but not stratum or cluster identifiers, the researchers approximated variance using a Kish design effect of 2.51, and they confirmed that their conclusions held when they recomputed key contrasts under design effects ranging from 2.0 to 3.0.

The weighted prevalence of disability in the sample was 9.3 percent, with sensory disability alone accounting for 57.4 percent of the group with disabilities, followed by physical only at 28.6 percent. Adults with disabilities were older (45.0 percent aged 60 or older, versus 19.7 percent of those without), more frequently women (55.8 percent versus 50.5 percent), and more frequently of low socioeconomic status (38.7 percent versus 31.0 percent). These demographic differences matter because they partially explain the crude inactivity gap: 40.5 percent of adults with disabilities were physically inactive compared with 27.0 percent of those without, a raw difference of roughly 13.5 percentage points that narrowed to a prevalence ratio of 1.22 after adjustment. The persistence of that association after controlling for demographics indicates a disability-specific disadvantage beyond age structure alone.

What makes the finding actionable is the barrier profile among non-users. Among the 634 adults with disabilities and 3,635 without who reported having available spaces but not using them, three barriers stood out as significantly more frequent in the disability group. Distance or difficulty of access was reported by 14.0 percent versus 7.7 percent (prevalence ratio 1.82; 95 percent CI 1.44 to 2.31). Lack of companionship was reported by 25.9 percent versus 16.8 percent (PR 1.54; 1.31 to 1.80). Presence of crime was reported by 26.4 percent versus 21.4 percent (PR 1.23; 1.06 to 1.44). Inadequate lighting was borderline (15.3 percent versus 12.2 percent; PR 1.25; p = 0.046). Notably, complaints about poor maintenance were actually less frequent among adults with disabilities (19.2 percent versus 23.5 percent; PR 0.82), which the authors interpret as evidence that the excess is not driven by a uniformly more negative perception of the environment but concentrates in barriers plausibly related to functional limitations: getting to the space and having support once there.

The heterogeneity across disability types adds another layer. Adults reporting multiple disability types showed the strongest association with non-use of available spaces (adjusted PR 1.47; 1.35 to 1.60), followed by cognitive only (1.29; 1.00 to 1.67), other only (1.20; 1.01 to 1.43), physical only (1.14; 1.05 to 1.24) and sensory only (1.09; 1.02 to 1.17). This ordering mirrors international evidence: among Spanish users of adapted sport programs, environmental barriers predominated in visual disability while intrinsic barriers predominated in physical and intellectual disability. The pattern is consistent with the global estimate that people with disabilities are 16 to 62 percent less likely to meet physical activity guidelines, a range that reflects precisely this heterogeneity across disability types and contexts.

The stratified analyses reveal a striking sex pattern. Disability appears to erase the male advantage in physical activity observed in the general population: men without disabilities were substantially more active than women without disabilities, but inactivity among adults with disabilities converged near 40 percent in both sexes. The interaction between disability and sex for inactivity was statistically significant (p = 0.009), with the crude prevalence ratio reaching 1.78 among men compared with 1.30 among women. Barrier profiles also diverged by group: lack of companionship weighed most heavily among adults aged 60 and over (30.5 percent versus 19.4 percent) and among men (27.7 percent versus 14.2 percent), while presence of crime was differential only among women (30.9 percent versus 24.3 percent). Distance or difficult access was elevated in nearly every stratum examined.

The policy implications are direct. Chile’s newly enacted National Policy on Physical Activity and Sport 2026-2037 acknowledges that 79.3 percent of persons with disabilities engage in no physical activity, citing the national disability survey, but delegates its quantified targets to forthcoming national and regional plans. The present findings suggest that building more infrastructure would not by itself close the gap, since perceived availability is already near universal in both groups. Instead, the actionable margins are accessibility audits and universal design retrofitting of existing spaces, safe route programs connecting homes to spaces, and accompanied or peer-supported physical activity schemes that directly target the three differential barriers identified. The authors also point to a comparatively low-cost complement: training physical education teachers, sport coaches and municipal staff in inclusive and adapted physical activity, so that existing spaces are staffed by professionals prepared to receive people with disabilities.

The study has limitations that the authors acknowledge candidly. Disability was self-reported through a brief dichotomous item battery without severity grading or use of the standardized Washington Group questions, which likely captures more severe cases; the 9.3 percent prevalence sits closer to the severe fraction of the III National Disability Study (ENDISC 2022), which estimates 17.6 percent of Chilean adults live with some degree of disability. The cognitive only group was small (n = 45), yielding wide confidence intervals. The residual

Subject of Research: Disability and use of physical activity spaces in Chilean adults

Article Title: Similar perceived availability but lower use of physical activity spaces among Chilean adults with disabilities

Article References: De Souza-Lima, J., Winckler, C., Olasagasti-Ibargoien, J., Yáñez-Sepúlveda, R., Godoy-Tapia, C., Parra-Saldías, M., Duclos-Bastías, D., Godoy-Cumillaf, A., Merellano-Navarro, E., Bruneau-Chávez, J., Reyes-Amigo, T., & Farías-Valenzuela, C. (2026). Similar perceived availability but lower use of physical activity spaces among Chilean adults with disabilities. Frontiers in Sports and Active Living, 8, Article 1969080. https://doi.org/10.3389/fspor.2026.1969080

Image Credits: AI Generated

DOI: 10.3389/fspor.2026.1969080

Keywords: physical activity, disability, Chile, built environment, accessibility, national survey, ENAFyD, public health, health equity, barriers, inclusive policy, Similar

The review, published on 14 August 2026, synthesizes literature on how Strategic Facilities Management (SFM) can translate high-level ESG commitments into concrete, facility-level actions. The authors ground their argument in Stakeholder Theory, the influential framework formalized by R. Edward Freeman in the 1980s, which holds that organizations create long-term value only when they balance the legitimate interests of all parties affected by their actions—employees, customers, suppliers, regulators, and local communities. Viewed through this lens, buildings are not merely physical assets to be maintained at minimal cost. They are social environments that shape employee wellbeing, inclusion, productivity, and community outcomes in measurable ways.

The evolution of facilities management itself tells a striking story. Emerging as a distinct management discipline during the 1980s and 1990s, FM was originally aimed at controlling and reducing costs through innovative methods of organizing diverse activities that had previously received minimal management attention. Over the following decades, the field transformed from a narrow, cost-focused operational function into a strategic discipline centered on value creation, sustainability, and stakeholder engagement. The International Organization for Standardization now defines FM as an organizational function that integrates people, place, and process within the built environment to improve quality of life and the productivity of the core business—a definition that signals a fundamental shift from asset maintenance to human-centered value creation.

Central to understanding this strategic potential is the FM Value Map, a framework that traces how facility-level inputs, processes, and outputs translate into outcomes for organizations and their stakeholders. The Value Map identifies three primary routes through which facilities management adds value: exchange value, encompassing cost savings, asset appreciation, and financial efficiency; use value, the benefits experienced by users including satisfaction, productivity, and wellbeing; and relational value, the enhanced relationships with stakeholders reflected in brand reputation, social responsibility, and trust. This structured logic provides the analytical backbone for the review’s proposed conceptual framework, which integrates Stakeholder Theory with SFM practice to guide the identification, implementation, and evaluation of social ESG outcomes.

The empirical evidence linking facility decisions to human outcomes is growing. In the South African context, research by Nurick and Thatcher demonstrated that indoor environmental quality in green-certified office buildings significantly influences the productivity and wellbeing of knowledge workers. Factors such as thermal comfort, lighting, acoustics, and air quality shape the workplace experience in ways that directly affect organizational performance. Other studies synthesized in the review connect healthy workplaces to employee satisfaction, productivity, and cost outcomes, strengthening the business case for social-oriented facilities strategies. Meanwhile, the FM profession’s reach extends well beyond the office: facilities managers translate strategic community plans into operational realities, manage shared amenities, and oversee contracts for cleaning, security, maintenance, catering, and waste management—each an opportunity for local economic inclusion.

Digital transformation is reshaping the governance dimension of this picture. Recent research highlights that SFM increasingly relies on Building Information Modeling (BIM) and the Internet of Things (IoT) to provide the granular data necessary for accurate ESG reporting, enabling facilities managers to transition from static annual reporting to dynamic performance management. But the review also flags a tension at the heart of this technological shift. As Nappi and de Campos Ribeiro caution, the same sensors that optimize workplace environments also create risks of surveillance and re-identification, positioning technology as both an enabler of social value through improved comfort and efficiency and a potential threat to privacy and trust.

The review identifies several major debates that define the field. The first concerns measurement: can social value be quantified with the same precision as environmental metrics? Porter and colleagues argue that the investment community already possesses the analytical tools to assess social performance and that the real obstacle is a lack of organizational commitment. Semet and Mandell counter that the tools themselves are the problem, pointing to the absence of standardized metrics, the subjective nature of social value, and the difficulty of attributing community outcomes to specific corporate actions. The Urban Land Institute similarly notes that no consensus exists on standardized methods for defining and quantifying social value. The stakes are high: if social value is deemed fundamentally unmeasurable, facilities management’s contribution to the social pillar will remain peripheral, whereas frameworks such as Social Return on Investment (SROI) could position SFM as a credible contributor to corporate sustainability reporting.

A second debate concerns the proper scope of facilities management’s social responsibility. Much of the literature focuses on internal stakeholders—employee wellbeing, occupant satisfaction, and productivity gains within the workplace—positioning FM as a support function that enhances human capital for the organization’s benefit. In contrast, other scholars contend that facilities managers have a role in fostering community prosperity, social justice, and local economic development. A third controversy pits standardization against context sensitivity: while some researchers advocate aligning FM operations with the United Nations Sustainable Development Goals to enable benchmarking and investor communication, others highlight the proliferation of inconsistent global rating systems and argue that sustainability is inherently socio-technical, emerging from local contexts and relationships that cannot be reduced to universal metrics.

The gap between strategic ambition and operational capability emerges as perhaps the field’s most persistent challenge. The review documents that FM departments often struggle to communicate their value in the language of executive leadership, lack the mandate and resources to operate at their full potential, and face inconsistent reporting standards with unclearly defined roles and responsibilities. Litvin emphasizes that technical systems alone are insufficient—what matters is the presence of trained professionals who can drive environmental and social agendas. Without investment in human capital and professional development, the strategic potential of SFM will remain unrealised. The proposed framework addresses this by offering facilities managers, corporate real estate teams, and ESG officers a structured approach spanning stakeholder identification, practice implementation, and outcome evaluation, with indicative metrics ranging from absenteeism rates and indoor environmental quality to procurement spend directed toward small and medium-sized enterprises.

The South African context gives these findings particular urgency. The country’s history of spatial planning created deeply entrenched inequalities in the built environment, with communities deliberately separated and economic opportunities concentrated in urban centers—inequalities that persist today in unequal access to employment, education, healthcare, and public amenities. In this setting, the social dimension of ESG carries a transformative imperative: corporate actors are expected to actively contribute to redressing historical inequities through their operations and investments, supported by robust governance codes and regulatory frameworks that place social outcomes at the center of organizational legitimacy. The authors conclude that SFM is well positioned to bridge the strategy execution gap in corporate ESG and strengthen socially responsive sustainability practices, while acknowledging that their framework remains conceptual and awaits empirical validation through case studies, comparative research across regulatory environments, and the development of robust measurement tools for social outcomes at individual, organizational, and community levels.

Subject of Research: Leveraging strategic facilities management to achieve corporate ESG and sustainability: a literature review

Article Title: Leveraging strategic facilities management to achieve corporate ESG and sustainability: a literature review

Article References: Nephawe, T. E., Nurick, S., & Michell, K. (2026). Leveraging strategic facilities management to achieve corporate ESG and sustainability: a literature review. Frontiers in Environmental Economics, 5, Article 1839120. https://doi.org/10.3389/frevc.2026.1839120

Image Credits: AI Generated

DOI: 10.3389/frevc.2026.1839120

Keywords: ESG, facilities management, social sustainability, stakeholder theory, built environment, corporate real estate, workplace wellbeing, Sustainable Development Goals, ethical procurement, South Africa, Leveraging, strategic

The study, led by Emmanuella A. Asiedu of the University of Miami’s Miller School of Medicine and UMass Chan Medical School, together with Jennifer Tjia, Jonggyu Baek, and Sarah N. Forrester of UMass Chan, focused on adults with electronically confirmed type 2 diabetes mellitus. The team used version 7 of the All of Us Registered Tier Dataset, covering the years 2017 through 2023, and restricted their analysis to participants who self-identified as either non-Hispanic Black or non-Hispanic White. That restriction was deliberate. Racial disparities in diabetes complications are well documented, and the researchers wanted to test whether the neighborhood environment modifies those disparities rather than simply averaging over them.

To quantify the built environment, the team turned to the Physical Activity Neighborhood Environment Scale, known as PANES, an instrument that scores neighborhoods from zero to eight based on features that support active living. A high-scoring neighborhood, in PANES terms, is one where homes are close to shops and services, where public transit is accessible, where sidewalks and bicycle infrastructure exist, and where parks and recreation facilities are within easy reach. The researchers grouped participants into three categories: those living in the least favorable environments with scores of zero to two, those in moderately favorable environments scoring three to five, and those in the most favorable environments scoring six to eight. This categorization allowed the team to compare clinical outcomes across a gradient of neighborhood walkability rather than treating the environment as a simple yes-or-no variable.

The clinical outcomes were drawn from linked electronic health records and represent the standard panel of measures that clinicians use to judge whether diabetes is under control. The primary outcome was high hemoglobin A1c, the blood test that reflects average glucose levels over the preceding two to three months and serves as the single most important indicator of diabetes management. The secondary outcomes included reduced estimated glomerular filtration rate, a marker of kidney function that declines as diabetic nephropathy advances; elevated low-density lipoprotein cholesterol, the lipid fraction most tightly linked to cardiovascular risk; and a set of EHR-documented conditions known to be related to type 2 diabetes. Psychological distress, defined as a score of five or higher on the Patient Health Questionnaire-9 or an electronic health record diagnosis of depression, was included as a potential modifier, since depression is known to worsen diabetes self-management and outcomes.

The headline number from the study is sobering: 89 percent of the study population had at least one adverse type 2 diabetes-related clinical outcome. That figure alone underscores how difficult it is to keep diabetes fully controlled even within a healthcare system, and it frames the central question of the research—if nearly everyone is struggling, what role does the environment around them play in determining who struggles most?

The answer, at first glance, was surprisingly muted. When the researchers ran modified Poisson regression models with generalized estimating equations, adjusting for sociodemographic factors, the crude and adjusted associations between PANES scores and the diabetes-related outcomes were not statistically significant across the population as a whole. In other words, living in a walkable neighborhood with parks and transit did not, on average, predict better A1c control, better kidney function, or better cholesterol levels compared with living in a less favorable environment. For advocates of walkable urban design, this null result might seem discouraging, but the story does not end there.

The interaction analyses revealed something the main models had obscured. When the researchers tested whether the relationship between the built environment and clinical outcomes differed by racial group, they found a statistically significant interaction for LDL cholesterol. Black individuals living in neighborhoods with the least favorable built attributes had a 43 percent greater prevalence of high LDL cholesterol compared with White individuals living in neighborhoods with the most favorable built attributes, with an adjusted prevalence ratio of 1.43 and a 95 percent confidence interval of 1.03 to 1.98. The interaction term p-value of 0.01 indicates that this difference is unlikely to be a statistical fluke. The effect modification by psychological distress, by contrast, did not yield significant findings in the reported results.

What does this mean mechanistically? The authors’ interpretation, grounded in their data rather than speculation, is that neighborhood contextual factors play a role in shaping cardiometabolic risk and that built environment inequities may exacerbate racial health disparities. The biological plausibility is straightforward. Neighborhoods lacking sidewalks, safe public spaces, and recreational facilities reduce opportunities for routine physical activity, which is one of the most effective non-pharmacological tools for improving lipid profiles and glucose control. Residents of such neighborhoods may also face longer exposure to stressors, fewer options for purchasing fresh food, and greater difficulty reaching healthcare appointments, all of which can compound the metabolic burden of diabetes. The fact that the disparity appeared specifically for LDL cholesterol—a marker strongly influenced by both diet and physical activity—fits this framework, though the cross-sectional design of the study means the data cannot establish that the environment caused the worse outcomes, only that the two are associated in a pattern consistent with that mechanism.

The methodological strengths of the study deserve attention. By using EHR-confirmed diabetes rather than self-report, the researchers avoided misclassification of the disease status. By linking standardized Observational Medical Outcomes Partnership-format records from the All of Us program, they accessed clinical measurements across a geographically diverse and demographically broad population, a sample far more representative than the single-health-system cohorts that dominate much of this literature. The use of modified Poisson regression with robust variance estimation is appropriate for binary outcomes with high prevalence, since standard logistic regression in such settings can produce prevalence ratios that overstate effect sizes. The formal interaction testing, rather than stratified analysis alone, gives the racial disparity finding a firmer statistical footing than a simple subgroup comparison would.

The limitations are equally worth stating plainly. The cross-sectional design captures a single snapshot, so reverse causation and time-varying confounding cannot be excluded. PANES scores, while validated, are a coarse summary of neighborhood quality and may miss features such as traffic safety, food access, or social cohesion that also shape health. The restriction to non-Hispanic Black and non-Hispanic White participants means the findings cannot be generalized to other racial and ethnic groups, including Hispanic and Asian populations who carry substantial diabetes burden. And the null overall association raises the possibility that neighborhood effects on diabetes outcomes operate through pathways or at spatial scales that PANES does not capture, or that individual-level factors such as medication access and healthcare quality dominate within this cohort.

Even with those caveats, the implications are concrete. The authors conclude that urban planning efforts prioritizing walkability, access to recreation, and safe public spaces—especially in underserved communities—are needed to support more equitable chronic disease outcomes. In practical terms, that means the tools for reducing diabetes complications may lie partly outside the clinic, in zoning decisions, transit investments, and park development that determine what a resident’s daily environment makes easy or hard. The 43 percent excess prevalence of high LDL cholesterol among Black residents of the least favorable neighborhoods is a quantified signal that the geography of diabetes is not evenly distributed, and that closing racial health gaps may require treating the neighborhood itself as a site of clinical intervention. As datasets like All of Us continue to grow and link environmental, genomic, and clinical data at scale, studies of this kind will increasingly be able to test whether reshaping the built environment actually reshapes the trajectory of chronic disease—a question with profound consequences for the millions of Americans living with diabetes in neighborhoods that were never designed with their health in mind.

Subject of Research: Association between neighborhood built-environment attributes and type 2 diabetes-related clinical outcomes, with effect modification by race

Article Title: Characterizing the association of neighborhood built-environment and type 2 diabetes-related clinical health outcomes: insights from the All of Us Research Program

Article References: Asiedu, E. A., Tjia, J., Baek, J., & Forrester, S. N. (2026). Characterizing the association of neighborhood built-environment and type 2 diabetes-related clinical health outcomes: insights from the All of Us Research Program. BMC Public Health. https://doi.org/10.1186/s12889-026-29830-8

Image Credits: AI Generated

DOI: 10.1186/s12889-026-29830-8

Keywords: type 2 diabetes, built environment, neighborhood walkability, All of Us Research Program, health disparities, LDL cholesterol, HbA1c, PANES, electronic health records, public health, urban planning, racial disparities

The scale of the problem gives the findings urgency. In 2010, an estimated 21 million men and 137 million women worldwide had a high probability of osteoporotic fracture, and that number is projected to nearly double to 319 million by 2040, with Asia accounting for 55 percent of those at high risk. By 2050, more than half of all osteoporotic fractures are expected to occur in Asia as the region’s population ages. Japan sits at the leading edge of this demographic shift: its share of residents aged 65 and older is projected to reach 37.7 percent by 2050, and in 2021 the country spent an estimated 1,278 billion yen on conditions related to bone density and structure and on fracture care for its aging population.

Researchers Qiaohui Zhou of Jinhua University of Vocational Technology and Riken Homma of Kumamoto University tackled the question with an unusually rich dataset. They obtained five years of fracture records—2017 through 2021—for 39,577 residents of Kumamoto Prefecture aged 75 or older, drawn from the Kumamoto Prefecture Senior Citizens’ Medical and Wide Area Alliance. Each person was assessed annually, and fracture occurrence was recorded as yes or no for each year, producing an ordered count from zero to five that represents how many years a fracture was recorded rather than clinical severity. Crucially, 98.51 percent of the participants were geocoded at the household level, allowing the team to work with fine-grained residential point data instead of the aggregated census tracts or towns that dominate most epidemiological studies.

To find fracture hotspots, the researchers used Kulldorff’s spatial scan statistics in an ordinal form, which preserves the ranked structure of the fracture counts rather than collapsing them into a simple case–control split. The method places a scanning window across the study area and identifies where the likelihood ratio test statistic reaches its maximum, with significance assessed through 999 Monte Carlo simulations. The team also applied a Gini coefficient procedure to optimize the maximum reported cluster size, settling on 20 percent as the optimal value. The scan revealed exactly two significant clusters: a high cluster in the northwest of the prefecture, covering the Tamana area and Yamaga city, and a low cluster northeast of Kumamoto city, encompassing Koshi city and Kikuyo town.

The two clusters differed sharply in both people and place. In the high cluster, only 74.3 percent of older adults had experienced no fracture over the five years, compared with 83.4 percent in the low cluster. Residents of the high-risk area were older on average, more likely to be women, and more likely to have reduced kidney function, low hemoglobin, dementia, and musculoskeletal disorders. They also reported poorer self-rated health, less satisfaction with daily life, slower walking speed, lower exercise rates, less social engagement, and more falls in the past year. The environment told a parallel story: the low cluster’s average population density was more than three times that of the high cluster, its intersection density more than twice as high, its walk score and mix of function nearly double, and its bus accessibility more than one and a half times greater, while the high cluster actually sat on steeper terrain.

For the statistical core of the study, the researchers turned to a zero-inflated ordered logit model, a technique designed for data crowded with zeros. The team reasoned that people with no fractures over five years belong to two latent groups: a genuinely non-susceptible excess group, and conditional zeros—people who did not fracture but might have if they had lived in less walkable neighborhoods or exercised less. The model therefore runs two processes at once: a binary logit that estimates the probability of being susceptible to fracture at all, and an ordered logit that models fracture frequency among those who are susceptible. This separation matters, because it allows the environment to influence whether someone ever fractures without necessarily changing how often fractures occur among the already vulnerable.

The results split cleanly along the cluster boundary. In the low cluster, no built environment attribute showed any significant association with either fracture occurrence or fracture frequency. In the high cluster, four attributes emerged as statistically significant protective factors for fracture occurrence. Population density was the strongest: older adults in the highest-density areas had odds of fracture occurrence only half those of people in the lowest-density areas, an odds ratio of 0.50 with a confidence interval of 0.35 to 0.71. Intersection density followed with an odds ratio of 0.64, bus accessibility with 0.75, and mix of function with 0.82, while walk score showed a marginal association at 0.75. Slope, by contrast, showed no significant relationship.

The pattern in the predicted probabilities reinforced the message. The probability of experiencing zero fractures rose steadily as walk score, mix of function, population density, intersection density, and bus accessibility increased, while the probability of one fracture fell consistently across the same gradient, with the most pronounced shifts seen for population density and then intersection density. Susceptibility estimates told a similar story: more than 35 percent of residents were susceptible to fracture when population density was zero, dropping below 25 percent at the highest densities, and comparable declines appeared for intersection density, walk score, bus access, and mix of function.

Why would the built environment matter in one place and not another? The authors point to context. Older adults in the low cluster were healthier overall—better physical performance, better oral function, fewer falls, and fewer musculoskeletal disorders—leaving less room for the environment to move the needle. The overall fracture incidence in the low cluster was also 9.1 percent lower than in the high cluster, which reduces statistical power to detect associations. In high-risk areas, by contrast, improving walkability may have more leverage: denser neighborhoods may offer better access to healthcare, more pedestrian-friendly infrastructure, and more social interaction that encourages physical activity, though the study did not directly test these mechanisms.

Notably, none of the built environment attributes was associated with fracture frequency among the susceptible group, suggesting that once someone is prone to fractures, individual factors such as bone density, frailty, and pre-existing musculoskeletal disorders may outweigh the influence of the neighborhood. The findings therefore point to a two-track strategy: urban planning that enhances density and street connectivity in high-risk areas to prevent first fractures, alongside individual-level interventions such as bone health screenings, strength training, and nutrition programs to reduce repeat fractures. The authors caution that the five-year window, cross-sectional covariates, separately modeled attributes, and baseline-only environment measurements limit causal interpretation, and they call for longitudinal studies with time-varying exposure data. Still, by pinpointing where fracture risk concentrates and which neighborhood features travel with it, the study offers local governments a concrete starting point for building neighborhoods that help older residents stay active, mobile, and unbroken.

Subject of Research: The relationship between neighborhood built environment attributes and fracture risk among older adults in high- and low-fracture clusters in Japan.

Article Title: Neighborhood built environment and fracture risk among older adults: comparing high versus low clusters

Article References: Zhou, Q., & Homma, R. (2026). Neighborhood built environment and fracture risk among older adults: comparing high versus low clusters. Frontiers in Public Health, 14, Article 1947343. https://doi.org/10.3389/fpubh.2026.1947343

Image Credits: AI Generated

DOI: 10.3389/fpubh.2026.1947343

Keywords: osteoporotic fracture, built environment, walkability, older adults, spatial scan statistics, population density, intersection density, bus accessibility, mixed land use, Japan, public health, aging

The team conducted a qualitative study at three Swedish RCFs, using a method well suited to its subject: walking interviews. Older residents were interviewed individually while moving through the spaces around them, and care workers took part in focus group walking interviews. Rather than asking people to recall their environment from a distant office, the researchers walked with them, allowing conversation to unfold in the very zones being discussed. This approach captured not only what participants thought about outdoor spaces but how they actually used, avoided, or imagined using them in daily care.

To organise the data, the researchers applied a model of four zones in contact with the outdoors. Zone 1 covers indoor environments with windows, the first point of visual contact with the outside world. Zone 2 comprises transitional outdoor environments, such as balconies, entrances and covered patios, where inside and outside meet. Zone 3 refers to gardens, the deliberately designed green spaces within the facility grounds, and Zone 4 encompasses the wider surroundings beyond the facility, from streets to parks to the broader landscape. Across each of these zones, the team identified everyday activities, care practices and rehabilitation opportunities, distinguishing between what currently happens and what could potentially happen.

The findings paint a picture of remarkable, largely unrealised potential. All four zones offered opportunities for social interaction, recreation, physical activity, contact with nature, health conversations, and even clinical assessments. A window view, in this framework, is not merely decoration; it is a site of stimulation and orientation. A balcony can host a morning coffee that doubles as a social encounter. A garden path can become a rehabilitation route where a physiotherapist or care worker supports walking practice in a setting far more engaging than an indoor corridor. The wider neighbourhood, meanwhile, opens possibilities for outings and maintained connection with the community beyond the facility walls.

Participants described a range of perceived benefits from outdoor engagement. These included stimulation, enjoyment, social interaction, sensory experiences, and contact with nature. For older adults, many of whom spend most of their time indoors, these experiences carry real weight. Sensory stimulation, the smell of plants, the sound of birds, the feel of sun and wind, is increasingly recognised as important for well-being in later life, particularly for people living with cognitive impairment. The study suggests that these benefits are not incidental extras but elements that could be deliberately harnessed as part of person-centred care and rehabilitation, approaches that tailor support to each individual’s preferences, capacities and life history.

Yet the gap between opportunity and practice was striking. The researchers found that the use of outdoor environments was limited by physical, seasonal, organisational, informational, and social barriers. Physical barriers might include steps, heavy doors, uneven surfaces or a lack of accessible routes, problems that turn a short garden trip into an ordeal for someone using a walker or wheelchair. Seasonal barriers are particularly acute in Sweden, where long winters and short daylight hours can make outdoor activity seem impractical for months at a time. Organisational barriers reflect the realities of care work: staff schedules built around indoor tasks leave little room for accompanying residents outside, and outdoor time is rarely treated as part of formal care delivery.

Informational and social barriers add further layers of complexity. If care workers lack knowledge about how outdoor spaces can support specific therapeutic goals, they are unlikely to incorporate them into care plans. And social dynamics matter too: some residents may hesitate to go outside without company, while staffing levels may mean no one is available to accompany them. The study’s central conclusion is that outdoor environments are a valuable but underutilised resource in RCFs, and that closing the gap requires more than good intentions. Integration into routine health service delivery, the authors argue, demands access to accessible environments, supportive organisational routines, and care workers with sufficient time, knowledge, and support.

What makes the study particularly useful is its practical orientation. By mapping activities and care practices across the four zones, and by distinguishing current practices from potential ones, the researchers have produced something like a catalogue of possibilities that facilities can adapt. The identified practices across the zones, they note, may provide practical inspiration for using outdoor environments in everyday activities and person-centred care and rehabilitation. For a care manager, the four-zone model offers a simple diagnostic tool: walk the facility from window to neighbourhood and ask what care activity could plausibly happen at each step, and what currently prevents it.

The implications extend beyond individual facilities. As populations age across Europe and beyond, the design and operation of residential care is under growing scrutiny, and health services research increasingly treats the built environment as an active component of care rather than a passive backdrop. This study fits within that shift, connecting architecture, landscape design and care practice. It also aligns with a broader evidence base linking green space and nature contact to health and well-being in older adults. By focusing specifically on how outdoor environments can be integrated into service delivery, rather than simply documenting their benefits, the Swedish team addresses a persistent blind spot: the organisational machinery that determines whether residents actually get outside.

The study was conducted with careful ethical oversight, approved by the Swedish Ethical Review Authority and carried out in accordance with the Declaration of Helsinki, with participation voluntary and informed consent obtained from all residents and care workers, including accommodations for participants with individual needs during the walking interviews. The work was funded by Forte, Formas, and the Kamprad Family Foundation for Entrepreneurship, Research and Charity, with open access funding provided by the University of Gothenburg. The research team drew together expertise from the Institute of Health and Care Sciences at the University of Gothenburg, the Division of Construction Management and Engineering at Chalmers University of Technology, and the Swedish University of Agricultural Sciences, a combination reflecting the study’s span across care science, building design and landscape research. For the older adults and care workers who took part, the message of the research is straightforward: the outdoors is not an amenity at the edge of care, but a resource that, with the right access, routines and support, belongs at the centre of it.

Subject of Research: Integration of outdoor environments into health service delivery at residential care facilities for older adults

Article Title: Integrating outdoor environments into health service delivery at residential care facilities for older adults

Article References: Liljegren, M., Bengtsson, A., Lindahl, G., & Wijk, H. (2026). Integrating outdoor environments into health service delivery at residential care facilities for older adults. BMC Health Services Research. https://doi.org/10.1186/s12913-026-15852-w

Image Credits: AI Generated

DOI: 10.1186/s12913-026-15852-w

Keywords: residential care facilities, older adults, outdoor environments, person-centred care, rehabilitation, health services research, care workers, gardens, everyday activities, built environment, geriatrics, Sweden

The research, led by Anoop Jain of Boston University School of Public Health together with Rockli Kim and S. V. Subramanian of Harvard University, analyzed data from the Longitudinal Aging Study in India, or LASI, a nationally representative survey covering all 36 states and Union Territories except Sikkim. From more than 72,000 respondents, the team focused on 63,564 women and men above the age of 45 who had complete information on the exposures and outcomes of interest. These individuals lived in 2,439 wards and villages, giving the researchers an unusually rich window into how conditions vary not just between people but between the communities they inhabit.

The methodological core of the study is its multilevel design. Rather than treating each respondent as an isolated data point, the researchers built a three-level statistical model in which individuals were nested within households and communities, and communities within states. The exposure of interest was the modeled proportion of people in each community living in households without any toilet, estimated using a Markov Chain Monte Carlo approach to produce an unconfounded community-level measure. Communities were then sorted into quintiles of toilet coverage, ranging from the lowest quintile, where fewer than 62 percent of residents had a toilet, to the highest, where more than 99 percent did.

Depression was measured with four widely used instruments. The first was the ten-item Center for Epidemiological Studies-Depression scale, known as CES-D, which captures symptoms such as feeling depressed, loneliness, low energy, and trouble concentrating over the past week; a score of four or above classified a respondent as having depressive symptoms. The remaining three measures came from the Composite International Diagnostic Interview Short Form, or CIDI-SF, a validated diagnostic screening tool translated into sixteen Indian regional languages. Respondents were classified as having probable major depression using three thresholds: the standard CIDI-SF cutoff, plus two stricter definitions requiring three or five of seven additional symptoms. The mean prevalence of CES-D symptoms in the sample was 28.1 percent, while probable major depression ranged from 7.1 to 8.9 percent depending on the definition used.

The results were striking. After adjusting for age, sex, marital status, education, caste, wealth, place of residence, and even the type of toilet in the respondent’s own household, people living in communities with the lowest toilet coverage had 38 percent higher odds of depressive symptoms on the CES-D scale than those in communities with the highest coverage, with an odds ratio of 1.38 and a 95 percent confidence interval of 1.08 to 1.76. The associations were even stronger for probable major depression: odds ratios of 1.58 for the standard CIDI-SF measure, 1.56 for the three-symptom definition, and 1.72 for the five-symptom definition, all statistically significant. Notably, the highest-coverage communities showed odds ratios close to one, suggesting no elevated risk relative to the reference group.

Perhaps the most provocative finding is what the study did not find. When the researchers examined the respondents’ own household toilet status, the associations with depression were weak and statistically indistinguishable from no effect. The odds ratios for living in a no-toilet household were 1.02 for CES-D and 0.99 for CIDI-SF. In other words, the community context appeared to matter more than the private one. This is a novel result, and the authors propose a plausible mechanism: in communities where nearly everyone lacks a toilet, residents have nowhere else to go, unable to borrow a neighbor’s facility or reach a public toilet block. In better-off communities, households without toilets may still access shared or public options, buffering them from the worst consequences of deprivation.

The cross-level interaction analysis added further nuance. Although none of the formal interaction terms reached statistical significance, the raw prevalence of depressive symptoms rose consistently across all household toilet types as community coverage fell. Among people with twin pit toilets, CES-D prevalence climbed from 12.6 percent in the highest-coverage communities to 27.0 percent in the lowest. Among those with pit latrines, CIDI-SF prevalence rose from 6.5 to 10.5 percent, and even among households with flush toilets, the three-symptom depression measure increased from 6.1 to 9.5 percent. The pattern suggests that a private toilet may offer less protection when the surrounding environment remains visibly degraded.

Why would community sanitation leave such a deep imprint on mental health? The authors point to several candidate pathways rooted in social science theory. One is spatial stigma: the idea that people living in visibly deprived places are marked by where they live, eroding their sense of self-worth, a phenomenon previously linked to depression in Japan and in Mumbai’s legally excluded settlements. Another draws on the broken windows hypothesis, in which visible signs of disorder, here open fecal contamination, signal that a place is neglected and uncontrolled, a perception consistently associated with psychological distress. A third pathway involves social division: sanitation programs such as Community-Led Total Sanitation have explicitly encouraged the use of shame to end open defecation, potentially fracturing community cohesion. The absence of sanitation is also associated with elevated risk of non-partner sexual violence, itself a driver of adverse mental health outcomes.

The study has honest limitations. The data are cross-sectional, collected in 2017 and 2018, so reverse causation and unmeasured confounding cannot be ruled out; communities with poor sanitation likely face other simultaneous deprivations, from poor schooling to caste-based discrimination, that the models could only partially capture. Toilet coverage has also expanded across India since the survey, meaning the analysis may overestimate current deprivation. LASI additionally does not ask whether people without household toilets use community or public facilities as substitutes. The authors call for future survey waves to probe these mechanisms directly, including questions on sanitation-related shame, visual disorder, and social division, and suggest that qualitative methods already used to study spatial stigma in India could illuminate the lived experience behind the statistics.

The stakes are enormous. India’s population over sixty is projected to double from 149 million in 2022 to 347 million by 2050, and 34.7 percent of those over sixty already report difficulty walking 100 yards, meaning many older adults spend most of their time within their immediate neighborhood. If the community around them is saturated with open defecation and the stigma it carries, their mental health may bear the cost. The authors argue that improving community-wide toilet coverage, not merely distributing household latrines, could become a concrete strategy for depression prevention, one that fits within India’s National Program for the Health Care of the Elderly and its vision of a society for all ages. In a field where mental health interventions often focus on the individual, this study is a reminder that sometimes the most powerful medicine for the mind is the environment outside the front door.

Subject of Research: The association between community-level toilet deprivation and depression among older adults in India

Article Title: Association between community toilet deprivation and depression among older adults in India: a multilevel analysis of the Longitudinal Aging Study in India from 2017-2018

Article References: Jain, A., Kim, R., & Subramanian, S. V. (2026). Association between community toilet deprivation and depression among older adults in India: a multilevel analysis of the Longitudinal Aging Study in India from 2017-2018. GeroScience. https://doi.org/10.1007/s11357-026-02537-9

Image Credits: AI Generated

DOI: 10.1007/s11357-026-02537-9

Keywords: sanitation, depression, older adults, India, LASI, multilevel analysis, built environment, mental health, toilet coverage, spatial stigma, public health, aging

A team led by Yiwei Yang of BOKU University in Vienna, together with colleagues at the Complexity Science Hub, Trier University, and the Max Planck Institute of Geoanthropology, took a radical methodological step. Instead of treating each city as a single data point—the so-called one-city-one-value approach—they chopped the entire contiguous United States into more than five million grid cells of one square kilometer each and treated every cell as an observation. Onto this lattice they layered some of the most detailed geospatial datasets ever assembled for the purpose: ten-meter-resolution maps of every building and piece of mobility infrastructure in the country, one-kilometer gridded greenhouse gas emissions from the Vulcan and DARTE inventories, and census-block population counts from 2020.

The mathematical heart of the study is the scaling law, a power relationship of the form Y = Y0 P^β, where an urban attribute Y grows with population P at an exponent β. When β exceeds one, the attribute grows super-linearly—doubling population more than doubles the attribute, as with income and patents. When β falls below one, growth is sub-linear: bigger populations need disproportionately less of the thing being measured. The researchers simply swapped cities for grid cells, asking how eighteen indicators—building footprints, floor areas, material masses, street areas, and emissions from residential, commercial, industrial, and on-road sources—scale with the population living in each cell.

The results are strikingly consistent. Residential building footprints, useful floor area, and material stocks scale moderately sub-linearly, with exponents between roughly 0.82 and 0.89. Non-residential buildings and mobility infrastructure scale far more steeply sub-linear, with exponents between 0.42 and 0.74. In practical terms, a grid cell with twice the population of its neighbor contains only about 1.9 times the building material, but just 1.5 times the mass of mobility infrastructure and roughly 1.35 times the street area. Roads, it turns out, are where density pays its biggest dividends: people packed closely together simply need far less pavement between them.

Greenhouse gas emissions follow the same logic, with an important sectoral twist. Residential building emissions and on-road transport emissions scale sub-linearly, at an average exponent of about 0.75, meaning a cell with double the population emits only around 1.7 times the carbon from homes and cars. The authors attribute this to the geometry of compact buildings—which have higher volume-to-surface ratios and therefore lower heating and cooling demand per unit of floor space—along with shorter trips and better public transport options. Commercial and industrial emissions, by contrast, scale nearly linearly, reflecting the fixed, energy-hungry operations of factories and offices that do not shrink much when surrounded by more people.

Translated into per capita terms, the findings become a blunt statement about the American landscape. Using benchmarks of roughly 50 people per square kilometer for rural areas, 600 for suburbs, and 1,800 for urban cores, the researchers calculate that residents of high-density urban cells need only 58 percent of the building footprint and a mere 17 percent of the mobility infrastructure area required by rural residents. Their combined building and infrastructure material stock is just 37 percent of the rural figure, and their residential and on-road emissions are 41 percent. Suburbanites sit in between, at roughly half to two-thirds of rural per capita levels. In short, people living in dense urban areas use half or less, per person, of nearly everything the built environment demands.

The study’s robustness checks are unusually thorough. The team tested sensitivity to grid placement, to assumptions about residential building heights and floor counts, and to spatial autocorrelation by comparing ordinary least squares with spatial lag and spatial error models—all with negligible changes to the estimated exponents. They subdivided the country into 15,600 windows of 30 by 30 kilometers and ran the regressions locally, finding that the exponents are distributed approximately normally around the national averages. A handful of anomalous windows, mostly in sparsely populated mountainous or rural terrain, showed super-linear or negative scaling, but these carried weak statistical reliability and did not disturb the overall pattern. Regional differences across the Northeast, South, Midwest, and West were statistically detectable but modest in practical magnitude.

Perhaps the most intellectually satisfying part of the paper is its explanation of why all this happens. Drawing on a fractal framework proposed by Molinero and Thurner, the authors interpret the scaling exponent as the ratio of the fractal dimension of infrastructure to that of population—essentially, how fully each occupies space across scales. Sub-linear scaling emerges when population fills space more completely than infrastructure does. This also explains why the exponents depend on scale: as grid cells grow larger, they capture more of the spatial complexity of the built environment, and the exponents drift upward toward city-level values. The team even found a compensatory trade-off—across all grid sizes, the exponents for street area and building footprint sum to a nearly constant value, a consequence of buildings and streets being forced to share the same finite two-dimensional land.

The comparison with conventional city-based analysis is where the study delivers its sharpest critique. Depending on which of four urban boundary definitions is used—compact urban centers, Census urban areas, morphological footprints, or functional commuting zones—city-level scaling exponents for emissions can flip from sub-linear to super-linear regimes, a long-standing embarrassment for the field. The grid-based approach sidesteps this arbitrariness entirely. It also reveals that the apparent per capita equality of building demand across cities of different sizes is an illusion produced by aggregation: city averages blend together low per capita demand in dense cores with high per capita demand in sprawling fringes, canceling each other out.

The policy implications are hard to escape. Because rural areas contain 1.7 times the total material mass, 3.2 times the mobility infrastructure area, and 1.3 times the on-road emissions of high-density urban areas despite a smaller total population, sustainability strategies aimed only at city cores will miss where much of the material and carbon burden actually sits. The authors argue that where, and at what density, new residents are accommodated is the decisive variable: prioritizing infill development, compact renewal, and efficient land use is central to any credible path toward lower material throughput and emissions. At the same time, they caution that material efficiency does not automatically translate into carbon efficiency—the transport sector’s emissions scale less favorably than its infrastructure, meaning that compactness must be paired with broader technological and social change. Whether these intra-settlement laws hold over time, and whether they generalize beyond the United States, remain open questions. But the message of this study is already clear: the greenest square kilometer in America is not the one with the biggest city around it, but the one with the most people sharing what has already been built.

Subject of Research: Scaling relationships between population density, built environment material stocks, service provisioning, and greenhouse gas emissions across the urban–rural continuum of the contiguous United States

Article Title: Intra-settlement scaling across the urban–rural continuum: material stocks, service provisioning, and greenhouse gas emissions in the contiguous United States

Article References: Yang, Y., Grammer, B., Prieto-Curiel, R., Frantz, D., Haberl, H., & Wiedenhofer, D. (2026). Intra-settlement scaling across the urban–rural continuum: material stocks, service provisioning, and greenhouse gas emissions in the contiguous United States. Journal of Industrial Ecology, 30(4), 1835-1849. https://doi.org/10.1007/s44498-026-00125-w

Image Credits: AI Generated

DOI: 10.1007/s44498-026-00125-w

Keywords: urban scaling laws, material stocks, greenhouse gas emissions, population density, built environment, mobility infrastructure, grid-based analysis, urban–rural continuum, fractal cities, sustainable urban development, industrial ecology, remote sensing

The study, led by Rajan Shrestha of Aarhus University and the Nepal Development Society, forms part of a growing effort to correct a stubborn imbalance in global health evidence. Physical inactivity and prolonged sedentary behaviour are rising public health concerns across low- and middle-income countries, where non-communicable diseases such as diabetes, cardiovascular disease and cancer are climbing steeply. Yet most of what researchers know about the environmental and psychological drivers of activity comes from high-income countries, and much of it rests on questionnaires that ask people to recall and report their own behaviour, a method notoriously prone to bias and error.

To sidestep those limitations, the researchers turned to objective measurement. They analysed data from 421 adults who had taken part in the Community-Based Promotion of Physical Activity trial in Pokhara Metropolitan City. Each participant wore an Axivity AX3 accelerometer on the wrist continuously for seven days, providing minute-by-minute records of movement and stillness. The device captures acceleration in three dimensions, from which researchers derive measures such as the Euclidean Norm Minus One, a standard metric for quantifying overall body movement intensity. From these raw signals, the team calculated daily moderate-to-vigorous physical activity, the intensity level most strongly linked to health benefits, as well as total sedentary time.

Alongside the sensor data, participants completed structured questionnaires covering two distinct categories of environmental opportunity. The first, described as recreational or built opportunities, captures features familiar from urban planning literature in wealthy countries: parks, playgrounds, walking paths, gyms and other purpose-built facilities for leisure-time exercise. The second, productive or utilitarian opportunities, reflects a different reality: whether the surrounding environment supports movement as a by-product of daily life, such as walking to markets, shops, workplaces or services. The team also measured psychosocial factors drawn from the Theory of Planned Behaviour, a widely used psychological framework, including intention to be active and perceived behavioural control, the confidence a person feels in their own ability to act.

Because participants were recruited through community clusters, the researchers used multilevel linear mixed-effects models with random intercepts for clusters, a statistical approach that accounts for the fact that people living in the same neighbourhood share characteristics and cannot be treated as fully independent observations. This matters enormously in studies of built environments: ignoring clustering can produce misleadingly confident estimates. The models estimated associations between environmental and psychosocial factors and two outcomes, daily moderate-to-vigorous physical activity and sedentary time, and the team added interaction terms to test whether perceived behavioural control modified the environmental effects.

The headline result is striking for what it reveals about the geography of movement. Productive and utilitarian environmental opportunities, the everyday infrastructure that lets people accomplish necessary tasks on foot, showed stronger associations with device-measured moderate-to-vigorous activity than recreational or built features did. In the model that considered the environment alone, higher productive or utilitarian opportunity was linked to more daily moderate-to-vigorous activity. However, when the researchers added psychosocial factors into a combined model, these environmental associations were attenuated, suggesting that part of the apparent environmental effect travels through, or overlaps with, psychological and motivational characteristics of individuals.

One psychological factor refused to fade. Perceived behavioural control remained positively and robustly associated with moderate-to-vigorous physical activity even after adjustment, with an estimated coefficient of 34.35 and a 95 percent confidence interval running from 6.98 to 61.72. In practical terms, adults who felt more capable of being active accumulated meaningfully more device-measured activity each day. Intention, by contrast, showed no clear association with measured behaviour, a finding that will resonate with anyone who has resolved to exercise and then not done so. The gap between intending and acting is a central puzzle of behavioural science, and this dataset from Nepal adds a low- and middle-income country data point to a debate dominated by Western samples.

Sedentary time told a subtler story. Environmental associations with sitting and stillness were weaker and less consistent than those with activity, but the interaction analysis produced one notable result: among people in the highest tertile of productive or utilitarian environmental opportunity, higher perceived behavioural control was associated with less sedentary time, with an interaction coefficient of −35.26 minutes and a confidence interval from −64.92 to −5.61. The interpretation is intriguing. Environments rich in utilitarian movement opportunities may only translate into less sitting for people who feel confident in their ability to act on those opportunities, hinting that environmental and psychological levers work together rather than independently.

The authors caution, appropriately, that this is a cross-sectional analysis. It captures a single moment in time and cannot establish whether environments shape behaviour, whether active people choose more supportive environments, or whether some third factor drives both. Reverse causation is a live possibility: someone who already enjoys walking may perceive their neighbourhood as more walkable. The sample, drawn from participants in an existing physical activity promotion trial in one metropolitan area, may also not represent all of semi-urban Nepal. Still, the use of objective accelerometry over a full week, the multilevel design and the explicit separation of recreational from productive environmental opportunity make this one of the more methodologically careful studies of its kind in South Asia.

The implications stretch well beyond Pokhara. Cities across Asia and Africa are urbanising at unprecedented speed, and the design choices made in the next two decades will lock in patterns of movement or stillness for generations. If the findings hold, they suggest that in rapidly urbanising low- and middle-income countries, promoting physical activity may depend less on importing the gym-and-park model of wealthy nations and more on preserving and strengthening the everyday, utilitarian movement woven into daily life, while simultaneously building residents’ confidence that they can act. Interventions that pair walkable markets, services and workplaces with behavioural support targeting perceived control could do double duty. As non-communicable diseases rise across the Global South, this study offers a timely reminder that the most powerful exercise prescription may already be written into the streets people walk every day, provided they believe they can follow it.

Subject of Research: Environmental and psychosocial determinants of device-measured physical activity and sedentary behaviour among adults in semi-urban Nepal

Article Title: Environmental and psychosocial contexts of device-measured physical activity and sedentary behaviour in semi-urban Nepal: a multilevel analysis

Article References: Shrestha, R., Paudel, S., Rijal, A., Adhikari, T. B., Khatri, B., Neupane, D., Vaidya, A., Nielsen, R. Ø., & Kallestrup, P. (2026). Environmental and psychosocial contexts of device-measured physical activity and sedentary behaviour in semi-urban Nepal: a multilevel analysis. BMC Public Health. https://doi.org/10.1186/s12889-026-29793-w

Image Credits: AI Generated

DOI: 10.1186/s12889-026-29793-w

Keywords: physical activity, sedentary behaviour, accelerometry, Nepal, low- and middle-income countries, built environment, perceived behavioural control, Theory of Planned Behaviour, multilevel analysis, public health, urbanisation, non-communicable diseases

The scientific motivation behind the study stems from a fundamental shift in how researchers think about physical activity, sedentary behaviour, and sleep. For decades, epidemiologists examined each of these behaviours in isolation, asking, for example, whether more exercise lowers the risk of heart disease or whether prolonged sitting raises the risk of type 2 diabetes. The evidence from such studies is clear: higher physical activity, less sedentary time, and adequate sleep are each associated with lower risks of cardiovascular disease, type 2 diabetes, obesity, several cancers, anxiety, depression, and premature mortality. But there is a hidden flaw in treating these behaviours separately. Time is finite. Every additional minute spent sitting is a minute not spent standing, stepping, or sleeping. The three behaviours are co-dependent components of a single twenty-four-hour whole, and analysing them independently distorts their true relationships with health.

This realisation has driven what researchers call the 24-hour movement paradigm, a framework that treats physical activity, sedentary behaviour, and sleep as inseparable parts of a daily time-use composition. The paradigm has already reshaped public health policy: several countries, including Canada, Australia, Thailand, South Africa, Saudi Arabia, and Egypt, along with the World Health Organization, have issued integrated 24-hour movement guidelines. Yet the first generation of these guidelines was built largely on studies that examined single behaviours in isolation, because rigorous evidence on their combined effects simply did not exist. The authors of the Canadian 24-hour movement guidelines for adults explicitly called for research with stronger designs, including longitudinal follow-up, device-measured behaviours, and attention to dimensions such as domain-specific activity, sleep consistency, napping, and daytime alertness. The Slovenian team designed the GIB study to answer exactly these calls.

The recruitment strategy leverages an existing national infrastructure. Every four years, the Statistical Office of Slovenia draws a nationally representative sample of 17,500 residents aged 18 to 74 from the Central Population Register, using stratified simple random sampling with region and settlement type as strata. These individuals are invited by post to complete the National Health-related Lifestyle Survey, conducted by the National Institute of Public Health, which historically achieves a response rate of around 60 percent. From the roughly 10,500 survey responders, the GIB team expects about 5 percent to accept an additional invitation to the device-based study, yielding approximately 525 participants per recruitment wave. The first baseline data collection took place in 2024, with subsequent waves planned for 2028, 2032, and beyond, creating a rolling cohort intended to span more than a decade.

At the heart of the measurement strategy sits the activPAL4micro, a small tri-axial accelerometer measuring just 4 by 2 by 0.4 centimetres and weighing 9 grams, which is attached to the front of the thigh. Unlike wrist-worn devices, thigh placement allows the monitor to distinguish posture with high precision: sitting, standing, lying, and stepping can be classified directly from body position rather than inferred from wrist movement. Participants wear the device for seven consecutive days, twenty-four hours per day, including during sleep, and simultaneously keep a diary recording bedtimes, wake times, naps, night-time awakenings, and, for employed participants, working hours. Sleep onset and offset are then determined by combining the algorithmic output with diary entries, with adjustments applied when the device records upright activity near the reported sleep window. The result is a complete, posture-based map of each participant’s entire week.

From these raw data, the researchers will construct two complementary time-use compositions. The first is posture-based, comprising stepping, standing, sitting, lying while awake, and sleeping. The second is movement-based, comprising moderate-to-vigorous physical activity, light-intensity physical activity, sedentary behaviour, and sleep. For employed participants, a third, domain-specific composition will separate occupational from non-occupational behaviour, allowing the team to ask whether physical activity at work carries the same health value as leisure-time exercise, a question with major implications for millions of workers in physically demanding jobs. Non-wear time will be proportionally reallocated to wake-time behaviours, daytime naps will be added to sleep time, and validated algorithms will process the event files in the R programming environment.

The device data will be complemented by an extensive battery of questionnaires. A novel ten-item instrument, the GIB24-Q, developed specifically for Slovenian population surveillance, asks about domain-specific moderate-to-vigorous activity, muscle-strengthening and balance exercise, walking, sedentary behaviour, recreational screen time, and sleep. The widely validated Global Physical Activity Questionnaire provides an international benchmark. The 46-item Healthy Built Environment Questionnaire captures perceptions of neighbourhood, home, and workplace environments, along with time spent outdoors and in nature. Each participant’s home address will also be linked to the Walk Score index, an open-access measure of neighbourhood walkability ranging from 0 to 100, and to environmental indicators including air quality and the number of days with high temperatures, enabling the team to test whether the places people live shape the way they move.

Well-being and health will be assessed through eight short validated instruments: the WHO-5 Well-being Index for subjective mental well-being, the Need for Recovery Scale for work-related fatigue, the International Fitness Scale for perceived fitness, the Epworth Sleepiness Scale for daytime sleepiness, the Fatigue Assessment Scale for chronic fatigue symptoms, the Satisfaction With Life Scale, the Perceived Time Poverty Scale, which measures the feeling of lacking freely disposable time, and the Nordic Musculoskeletal Questionnaire for pain across nine body regions. In parallel, each participant’s data will be linked to the National Health-related Lifestyle Survey, which covers demographics, diet, smoking, alcohol, self-rated health, diagnosed conditions, medication use, stress, social support, body mass index, and waist circumference. From 2028 onward, with additional informed consent, the team will link records to national registers covering healthcare utilisation, hospitalisations, drug prescriptions, sickness absence, retirement, disease incidence, and causes of death, all under strict data protection law and GDPR compliance.

The statistical approach is as innovative as the data collection. Because the components of a 24-hour composition are co-dependent, conventional regression is inappropriate; the team will instead apply compositional data analysis, expressing time-use as sets of isometric log-ratio coordinates before entering regression models, handling zeros with a log-ratio expectation-maximisation algorithm, and applying survey weights to preserve national representativeness. An a priori power analysis determined that the expected sample of roughly 472 participants per wave providing valid accelerometer data is sufficient to detect a minimum effect size of 0.2 with 80 percent power. For significant findings, the researchers will map what they call the Goldilocks Zone: the range of 24-hour movement compositions, estimated at ten-minute granularity, associated with the best 5 percent of predicted health outcomes, and will search for compositions that fall in the optimal zone across multiple health outcomes simultaneously.

The potential payoff is considerable. The GIB study will deliver the first device-measured estimates of 24-hour movement behaviours in a national sample of Slovenian adults, identify the socio-demographic and environmental factors that shape healthy and unhealthy time use, and clarify the relative importance of occupational versus leisure activity, sleep regularity, and specific postures for long-term health. As Slovenia develops its own 24-hour movement guidelines, the findings will provide directly relevant, population-specific evidence, and the team anticipates contributing data to international consortia pooling thigh-worn accelerometer records worldwide. If the study succeeds in defining Goldilocks Zones for daily time use, the humble question of how a nation spends its twenty-four hours could yield some of the most actionable health guidance of the coming decade.

Subject of Research: A longitudinal population-based study of 24-hour movement behaviours, their correlates, and health associations in Slovenian adults

Article Title: Prevalence, correlates, and health associations of 24-hour movement behaviours in Slovenian adults: a protocol for a longitudinal population-based study

Article References: Kastelic, K., Knific, T., & Šarabon, N. (2025). Prevalence, correlates, and health associations of 24-hour movement behaviours in Slovenian adults: a protocol for a longitudinal population-based study. Journal of Activity, Sedentary and Sleep Behaviors, 4(1), Article 3. https://doi.org/10.1186/s44167-025-00073-z

Image Credits: AI Generated

DOI: 10.1186/s44167-025-00073-z

Keywords: 24-hour movement behaviours, physical activity, sedentary behaviour, sleep, compositional data analysis, accelerometry, longitudinal study, population health, built environment, well-being, Slovenia, movement guidelines