Population Growth Research Articles

Grow or die! Land-use strategy mismatch in the ‘post-political’ metropolitan planning era

Metropolitan spaces are perceived as spatiotemporally dynamic entities where traditional settlement patterns transform into heterogeneous post-suburban forms, integrating complex networks of social and economic relationships. Inadequate coordination in local spatial planning is commonly seen as a crucial factor contributing to landscape fragmentation and persistent urban sprawl. The current ‘post-political’ era of metropolitan planning supposedly offers less formalized problem-solving approaches that are not burdened by institutionally fixed settings and excessive bureaucratic structures. However, it is not clear whether and how integrated metropolitan strategies emerging within the ‘soft spaces’ of governance can influence the local spatial strategies of individual municipalities and what spectrum of attitudes various stakeholders in the metropolitan area hold towards spatial and population growth. The main research question is: What differences in approaches to territorial and population development of settlements in the metropolitan area are observed from the perspective of various public administration actors? Using a case study of the Brno Metropolitan Area (Czech Republic) and employing quantitative spatial analysis of recent and planned population and spatial development, along with qualitative textual analysis of planning documentation rationale at various scales impacting the metropolitan area, this article elucidates the narratives typically underpinning pro-growth planning strategies. Additionally, it contextualizes the meanings attributed to the metropolitan dimension of development at the local level. The findings suggest a negligible impact of integrated metropolitan strategy on local land-use policies. Competitive mechanisms of municipal spatial planning contradicting metropolitan authority visions exacerbate the crisis of spatial identities and residential cannibalism. Population growth in the hinterland triggers narratives of inevitability, adaptation, smart growth, economic rationality, and population rejuvenation at the local planning level, culminating in land oversupply. The results provide urban policies with an explanatory framework for the diversity of attitudes towards spatial and land-use planning within the multi-scale metropolitan arena and argue for the introduction of more effective integrated metropolitan spatial planning tools.

A Fermatean Fuzzy SWARA-TOPSIS Methodology based on SCOR model for Autonomous Vehicle Parking Lot Selection

Population growth in crowded cities and the resulting increase in vehicle use have led to the problem of insufficient parking. When public parking lots and urban growth are not in coordination, vehicles park on the street and close the crosswalks. In the coming years, this problem will become more complicated with the addition of autonomous vehicles (AVs) to urban traffic. This study addresses the research question of how to effectively select AV parking lots in urban areas experiencing population growth and increased vehicle usage. For this aim, a hybrid Multi-Criteria Decision Making (MCDM) methodology, combining SWARA (Step-wise Weight Assessment Ratio Analysis) and TOPSIS (Technique for Order Preference by Similarity) approaches in a Fermatean Fuzzy (FF) environment is proposed. The decision hierarchy based on the SCOR model has been developed to determine and construct the evaluation criteria. Then, a case study analysis has been applied to selected districts in Istanbul, which is Turkiye's most populous and developing city. Operating expenses, safety and security, and land costs are determined as the most important factors. As a result of the detailed fuzzy analysis, which districts should primarily be chosen for AV parking lots in Istanbul is determined and finally, the robustness and validity of the results obtained by the sensitivity analysis being questioned. The study contributes by providing insights into AV parking lot selection, demonstrating the efficacy of the proposed methodology, and highlighting the importance of addressing this issue in urban planning.

Pecan (Carya illinoinensis (Wangenh.) K. Koch) nuts as an emerging source of protein: extraction, physicochemical and functional properties.

The increasing demand for sustainable alternatives to traditional protein sources, driven by population growth, underscores the importance of protein in a healthy diet. Pecan (Carya illinoinensis (Wangenh.) K. Koch) nuts are currently underutilized as plant-based proteins but hold great potential in the food industry. However, there is insufficient information available on pecan protein, particularly its protein fractions. This study aimed to explore the physicochemical and functional properties of protein isolate and the main protein fraction glutelin extracted from pecan nuts. The results revealed that glutelin (820.67 ± 69.42 g kg-1) had a higher crude protein content compared to the protein isolate (618.43 ± 27.35 g kg-1), while both proteins exhibited amino acid profiles sufficient for adult requirements. The isoelectric points of protein isolate and glutelin were determined to be pH 4.0 and pH 5.0, respectively. The denaturation temperature of the protein isolate (90.23 °C) was higher than that of glutelin (87.43 °C), indicating a more organized and stable conformation. This is further supported by the fact that the protein isolate had a more stable main secondary structure than glutelin. Both proteins demonstrated improved solubility, emulsifying, and foaming properties at pH levels deviating from their isoelectric points in U-shaped curves. Compared to the protein isolate, glutelin displayed superior water and oil absorption capacity along with enhanced gelling ability. The protein isolate and glutelin from pecan nuts exhibited improved stability and competitive functional properties, respectively. The appropriate utilization of these two proteins will support their potential as natural ingredients in various food systems. © 2024 Society of Chemical Industry.

Predictors of Fertility Desire During COVID-19 Pandemic: A Cross Sectional Study

Background: Fertility, the most important factor in population growth, is affected by various factors, including pandemics. COVID-19 (CV) was a global challenge that spread rapidly around the world. Objective: This study aimed to investigate predictors of fertility desire during the covid virus pandemic. Methods: In this cross-sectional study, 315 women who visited health centers in northern Iran for vaccination against covid virus were recruited using convenient sampling. The participants completed the sociodemographic information, Fertility Desire Scale, and Fear of covid virus scale. Logistic regression analysis was employed to assess the predictive factors of fertility desire. Results: The participants' mean age and marriage duration were 34.4 ± 6.7, and 7.3±11.5 years, respectively. It showed fertility desire among household women was about twofold more compared to employed ones [Odds Ratio (OR) = 1.96, p = 0.009)]. The fertility desire was decreased among more educated women (OR = 0.43, p= 0.035), women with one child (OR = 0.44, p= 0.030), and women with no infant gender preferences (OR = 0.53, p= 0.032). Fear of covid virus and any history of covid virus infection in the participants or their close relatives did not change fertility desire (P > 0.05). Conclusion: In conclusion, health policymakers should pay more attention to the potential effects of women's employment, their educational status, and their attitude toward infant gender preferences on fertility desire during the development of programs. Further research is needed to examine this empirical association on a global scale and its effect on trying to conceive.

A machine learning approach to map the potential agroecological complexity in an indigenous community of Colombia

Agroecological systems are potential solutions to the environmental challenges of intensive agriculture. Indigenous communities, such as the Kamëntšá Biyá and Kamëntšá Inga from the Sibundoy Valley (SV) in Colombia, have their own ancient agroecological systems called chagras. However, they are threatened by population growth and expansion of intensive agriculture. Establishing new chagras or enhancing existing ones faces impediments such as the necessity for continuous monitoring and mapping of agroecological potential. However, this method is often costly and time consuming. To address this limitation, we created a digital map of the Biodiversity Management Coefficient (BMC) (as a proxy of agroecological potential) using Machine Learning. We utilized 15 environmental predictors and in-situ BMC data from 800 chagras to train an XGBoost model capable of predicting a multiclass BMC structure with 70% accuracy. This model was deployed across the study area to map the extent and spatial distribution of BMC classes, providing detailed information on potential areas for new agroecological chagras as well as areas unsuitable for this purpose. This map captured footprints of past and present disturbance events in the SV, revealing its usefulness for agroecological planning. We highlight the most significant predictors and their optimal values that trigger higher BMC status.

Machine Learning Based Prediction of Compressive and Flexural Strength of Recycled Plastic Waste Aggregate Concrete

In the last 50 years, the use of plastics has increased significantly due to advances in technology, population growth and increasing needs. However, this trend has led to the accumulation of large amounts of plastic waste. Numerous studies have been conducted on the use of recycled plastic materials in concrete production as a means of recycling and environmental protection. This study aims to predict the 28-day cylinder compressive and flexural strength of concretes using Polyethylene Terephthalate (PET), Phenolic Formaldehyde (PF), Polypropylene (PP), Polycarbonate (PC), Polyvinyl Chloride (PCV), High-Impact Polystyrene (HIPS) and High-Density Polyethylene (HDPE) plastic waste as aggregates. In this scope, a comprehensive database was created using experimental results obtained from the literature. Then, this study used six ML models, including Support Vector Regressor (SVR), Random Forest Regressor (RFR), Gradient Boosting Regressor (GBR), XGBoost Regressor (XGR), LightGBM Regressor (LGR), Bagged Decision Trees Regressor (BDTR), to predict the compressive and flexural strength of recycled plastic waste aggregate concrete (RPWAC). From the experimental database, 253 data points with strength between 6.00-70.05MPa were identified to estimate the compressive strength (CS) and 175 data points with strength between 1.21-7.96MPa were identified for flexural strength (FS). Cross-validation was used for six ML models and hyperparameter fine-tuning was performed. The results showed that six different ML models predicted the compressive and flexural strengths of RPWAC with high accuracy. The XGR model predicted CS and FS better than the other five different models with R2 values of 0.931 and 0.999, respectively. The three main properties effecting the CS of RPWAC were plastic waste content, water/cement ratio and concrete specific gravity, while the three main properties affecting the FS of RPWAC were cement specific gravity, plastic waste content and cement CS.

Immunosuppressive Therapy, Puberty and Growth Outcomes in Pediatric Kidney Transplant Recipients: A Pragmatic Review.

Kidney transplantation in children with end-stage kidney disease significantly enhances survival and quality of life but poses unique challenges related to chronic immunosuppressive therapy. In fact, despite being essential for preventing organ rejection, immunosuppressive therapy can have significant side effects specific to pediatric patients, such as adverse impacts on physiological growth, puberty, and fertility. The resulting short stature and delayed or incomplete pubertal development can profoundly affect young patients' psychological and social well-being, impacting self-esteem and overall quality of life, and may significantly hamper compliance and therapeutic adherence. Most studies on immunosuppression in pediatric kidney transplant recipients focus on general side effects and outcomes like long-term graft survival or acute complications. On the other side, there is limited evidence in the current literature on the specific issues of growth, puberty, and fertility in this patient population. In this pragmatic review, we aimed to summarize the most relevant information available on these critical aspects of post-transplant management in pediatric patients, also providing some practical indications on management strategies for minimizing these often neglected but still important complications.

IoT-enabled smart cities towards green energy systems: a review

<span>Integration of internet of things (IoT) in smart city management to improve various functions and living standards due to increasing population growth has dramatically evolved ubiquitous and essential services at various stages of urbanization. Hence, smart cities need to be eco-friendly by improving various sectors like education, health, and transport to provide an urban and sustainable quality of life through solving complicated green energy networks, controlling toxic pollution risks, and public safety. Linking optimized green energy systems with the production and automation of advanced applications is crucial to compose implementation strategies for smart city services. This paper aims to conduct a review on eco-friendly plans and infrastructure of IoT-enabled smart cities by exploiting green energy approaches. This study performs critical observations, ideas, and analyses of recent research in the context of our mentioned research theme. This paper points out the technical and functional challenges of an optimal performance-based green IoT-enabled smart city infrastructure. In this sense, this study organizes observations of relevant initiatives, technologies, and experiences in IoT-enabled smart cities, as well as how to embed it with green energy. Moreover, it can provide significant directions to intellectuals and authorities to develop IoT-enabled smart city applications for prospective research.</span>

A novel blockchain-based system for improving information integrity in building projects from the perspective of building energy performance

Global population growth has long been intertwined with environmental concerns and sustainable development. The building sector, a significant energy consumer worldwide, contributes substantially to total energy consumption and greenhouse gas emissions. With the projected global population projected to reach 9.7 billion by 2050, building energy consumption is expected to rise continuously, emphasizing the need to optimize energy performance for environmental sustainability. Despite efforts by many countries to formulate energy conservation objectives and strategies, empirical evidence reveals a substantial disparity between designed and actual building energy consumption, known as the building energy performance gap (BEPG). This gap poses a significant challenge to energy conservation efforts, and the lack of information integrity is a significant contributor to this gap. To address the challenge of inadequate information integrity in building energy projects, this research proposes an innovative solution based on blockchain technology. By utilizing blockchain's decentralized, transparent, and tamper-resistant nature, the proposed model aims to enhance information transmission mechanisms among stakeholders. Ten key energy-related stakeholders and various information flows within building projects are identified. Based on this, an exploratory architectural information management model incorporating blockchain technology is developed. The model features functionalities such as data recording, retrieval, transmission, and incentive mechanisms to ensure data immutability and reliable access security. Through a case study, the model's performance is evaluated in terms of storage cost, latency, and privacy, demonstrating significant time savings in uploading and transferring files. The proposed blockchain-based model offers a feasible solution to the challenges of inadequate information integrity in building energy projects, promoting collaboration and accurate information transmission. This model contributes to improving project outcomes and advancing sustainable development in the construction industry.

A Concentrated Analysis of the Situation of Flood Control Management: A Review

Floods are happening more often and with greater severity due to socioeconomic development and climate change. Flood control is widely acknowledged as an effective means of reducing the negative effects, and recent research has aimed to develop a more robust and sustainable approach to flood management. A thorough bibliometric examination of terms, keywords, and dates in the flood research field was employed in this work. It provides new insight into the flood research trends, by examining the research frontiers from 2000 to 2021. We conclude that there has been a shift in the focus of flood research from flood management to flood resilience. Flood resilience management offers a more resilient and sustainable plan to deal with flood disasters, while flood risk management offers an adaptation approach by adjusting mitigation measures. The review demonstrates how flood research has progressed from traditional flood management, which provides mitigation strategies, to flood resilience management. Along with reviewing the definition of risk, risk analysis techniques, flood resilience, flood management, and flood risk management, we also provide a thorough introduction of the field of flood research. We come to the conclusion that a preferable strategy for future flood control directions is to incorporate the idea of resilience into the risk management framework. Consequently, employing the theories of risk, resilience, and sustainability, sensible choices and actions made before, during, and after a disaster will successfully minimize the negative effects. Devastating floods brought on by swift urbanization and severe weather patterns have claimed millions of lives and continue to inflict direct economic losses estimated at tens of billions of dollars annually. Furthermore, as extreme precipitation events intensify (Tabari, 2020) and the population at risk of water-related disasters rises (Jongman et al., 2012; Paudel et al., 2014; Tellman et al., 2021), these losses will only rise in the future due to global warming (Bloeschl et al., 2019; CRED and UNISDR, 2020; Hallegatte et al., 2013). Even worse, severe compound flooding from excessive river flow, intense rainfall, and storm surges might arise from the simultaneous occurrence of flash floods, river flooding, urban flooding, and coastal flooding (Ming et al., 2022). Given that the causes of coastal, urban, and river flooding vary, determining the locations most vulnerable to these types of floods is a challenging. While flood risk is known to rise in response to population growth, climate change, and the accumulation of economic assets, it is also known that this risk is dynamic and ever-changing due to changes in underlying surface conditions (Hallegatte et al., 2013; Lai et al., 2020). Thus, it is critical to manage flooding in order to address the rising risk of flooding. Prior studies have demonstrated the pressing need to address flood events (da Silva et al., 2020), and future flood mitigation measures must be developed in order to lessen the negative effects and handle increasingly complicated flood kinds.

Analysing forced migration’s impact on Ukraine’s economic sustainability

Purpose. To characterize consequences of forced migration from Ukraine to European countries, quantifying its impact on economic growth, the number, income of the economically active population, investment and industry of Ukraine, and to develop recommendations for overcoming the negative economic effect of migration. Methodology. The methods of analysis and synthesis, scientific abstraction, statistical analysis, economic and mathematical modeling, and graphical analysis were used. Findings. The article studies the factors that caused forced migration from Ukraine’s to European countries as well as the main differences in migration processes provoked by Russia’s war against Ukraine are substantiated. The economic effects and consequences of its impact on the Ukrainian economy are analyzed. The study is based on statistical data characterizing economic growth (GDP) and the factors that determine it (capital investment, economically active population). On the basis of the Cobb-Douglas production function with neutral scientific and technological progress or Hicks scientific and technological progress and the use of linear regression analysis methods, the relationship between changes in the number of economically active population and economic growth is established. Originality. A forecast of changes in GDP under the influence of forced migration of the economically active population of Ukraine in 2023 is calculated and three main scenarios of GDP dynamics are developed in accordance with these forecasts. Each of them envisages a significant drop in output under the influence of migration. Practical value. The article proposes ways to address the problem of forced migration in Ukraine’s economy and the consequences of its negative impact on sustainable development based on the experience of European countries. Ways to restore industry and attract investments to Ukraine are substantiated.

Ciphering of greenhouse gases from constructed wetlands in Lucknow (U. P. India)

This study evaluates how greenhouse gases (GHGs) contribute to global warming, drawing attention to the substantial effect of human activity on GHG concentrations in the atmosphere. The lower atmosphere warms as a consequence of the absorption as well as the emission of thermal infrared radiation by greenhouse gases, which are both naturally occurring and created by human beings. Since the 1950s, it has been determined that carbon dioxide (CO2) contributes a vital part in tweaking the environmental conditions, with other gases which include methane (CH4), nitrous oxide (N2O), and CFCs also playing a significant role. India is the third-biggest producer of greenhouse gases (GHGs) due to its enormous population and fast economic growth. This study looks into the GHG emissions from manmade wetlands (CWs) and seasonal assessments conducted in Lucknow and the neighboring wetlands. The emissions of nitrous oxide and methane from CWs are computed using particular formulas and parameters. Utilizing particular formulas and parameters, the emissions of methane and nitrous oxide from CWs are computed. The results emphasize the significance of efficient management techniques such as hydrological control, organic matter control, intermittent drying, shading, adding biochar, and hybrid systems in reducing greenhouse gas emissions from wetlands. The mitigation of the ecological consequences of chemical warfare and the fight against global warming necessitates these protocols.

Urban green spaces and public realm design in Cairo: Enhancing quality of life and environmental sustainability

The paper explores the pressing challenges and promising initiatives in enhancing urban green spaces and the public realm in Cairo, a metropolis grappling with rapid population growth and environmental degradation. As the city struggles with density, air pollution, and a shortage of green areas—far below the recommended standard for urban health—the article highlights key efforts to revitalize public spaces. Notable projects include the creation of large parks like Al-Azhar Park, the redevelopment of the Nile riverfront through projects such as Mamsha Ahl Misr, and the introduction of green infrastructure solutions like street trees, green roofs, and sustainable urban drainage systems. Despite these advancements, Cairo faces significant obstacles, including limited public land, budget constraints, and water scarcity. However, there are opportunities to address these challenges through innovative urban agriculture, public-private partnerships, and community participation in green space development. The paper suggests that through continued investment and thoughtful urban design, Cairo can foster a more sustainable, livable environment. By integrating green infrastructure into future development projects, the city holds potential to transform its landscape and improve the quality of life for its residents in the coming decades.

A hybrid finite element method for moving-habitat models in two spatial dimensions

Moving-habitat models track the density of a population whose suitable habitat shifts as a consequence of climate change. Whereas most previous studies in this area consider 1-dimensional space, we derive and study a spatially 2-dimensional moving-habitat model via reaction-diffusion equations. The population inhabits the whole space. The suitable habitat is a bounded region where population growth is positive; the unbounded complement of its closure is unsuitable with negative growth. The interface between the two habitat types moves, depicting the movement of the suitable habitat poleward. Detailed modelling of individual movement behaviour induces a nonstandard discontinuity in the density across the interface. For the corresponding semi-discretised system we prove well-posedness for a constant shifting velocity before constructing an implicit-explicit hybrid finite element method. In this method, a Lagrange multiplier weakly imposes the jump discontinuity across the interface. For a stationary interface, we derive optimal a priori error estimates over a conformal mesh with nonconformal discretisation. We demonstrate with numerical convergence tests that these results hold for the moving interface. Finally, we demonstrate the strength of our hybrid finite element method with two biologically motivated cases, one for a domain with a curved boundary and the other for non-constant shifting velocity.

Exploring the Potential of Agriculture Diversification as a Pathway to an Improved Smallholder Livelihood Dietary System in Nepal

Agriculture, a cornerstone of Nepal’s economy, is dominated by smallholder farmers cultivating staple crops under resource and input constraints, leading to declining productivity amid rapid population growth and urban migration. This study explores the role of agricultural diversification in enhancing dietary diversity and improving smallholder livelihoods using panel data from the Nepal Household Risk and Vulnerability Survey (2016–2018). Analysis through the Simpson diversification index and food consumption scores reveals a strong positive correlation between agricultural diversification and dietary diversity. Key determinants include market access, irrigation systems (rainfed or canal-based), input availability (fertilizers and labor), and land type. Dry season crop diversification was positively associated with dietary diversity, while market access showed a significant negative impact on dietary diversity as distance increased. Upland areas exhibited higher potential for diversification, especially in the dry season, driven by improved access to inputs and irrigation. Policy recommendations highlight the need to enhance infrastructure in upland regions, improve market access, and ensure input availability, particularly fertilizers and labor, to support seasonal diversification. Such measures are essential for strengthening food security, nutritional diversity, and economic resilience among smallholder farmers in Nepal.

Linear Regression-Based Traffic Flow Simulation: Vehicle Density and Speed Analysis on Buah Batu Road

Traffic congestion has become an increasingly severe problem in many major cities around the world, including in the city of Bandung. Population growth and increased vehicle use exacerbate congestion. Jalan Buah Batu, one of the main roads in the city of Bandung, often experiences congestion due to high density. This study explains the traffic flow simulation using the Lighthill-Whitham-Richards (LWR) model with a speed-density function obtained from observation data on Jalan Buah Batu, Bandung. The data included the relationship between vehicle density and speed which was then analyzed using the linear regression method. The approximation of the velocity-density function obtained from linear regression is v(ρ)= -6.904+4.302. Traffic flow simulations were carried out with a road length of 60 meters, a total time of 5 minutes, and high resolution with 300 grid points. At the beginning of the simulation, a peak density of 0.70 occurred in a 15-25 meter road segment. Over time, the peak density shifted and decreased: 0.65 at 20-30 meters at 1.25 minutes, 0.60 at 25-35 meters at 2.5 minutes, and 0.50 at 30-50 meters at the end of the simulation (5 minutes). These results show the movement of vehicles that reduce congestion and improve the smooth flow of traffic. In conclusion, linear regression is effective in determining the velocity-density function.

The Future Politics of Social Protection in Africa

International organisations and their local allies continue to press for the further expansion of social protection across Africa, often in the face of resistance. The future politics of social protection in Africa will be shaped by endogenous and exogenous changes. Endogenous changes involve feedback effects from the past and continuing expansion of social protection; these can be either positive or negative in terms of further expansion. Exogenous effects result from the changing structural context, including especially population growth, urbanisation, and climate change. As the Covid-19 pandemic and related lockdowns showed, even those exogenous shocks which reveal gaps in current provision need not prompt enduring expansions of social protection. Neither endogenous nor exogenous changes are likely to shift African countries off their current varied pathways; considerable political obstacles to the further expansion of social protection will persist.

One Health Perspectives on Food System Transformation: Insights from the InsectERA Agenda

Abstract Background One Health framework recognises the interconnectedness of human, animal, plant and environmental health. With this understanding, it becomes imperative to address challenges such as those posed by food systems through a One Health lens. Food systems pose significant public health challenges, particularly in terms of food safety and security. Pressures from factors such as population growth, changing consumption patterns and intensified production systems, particularly animal-based protein production, contribute to environmental pressures. In addition, environmental changes, including climate change, further threaten food safety and access to healthy food. Methods Through the InsectERA agenda, funded as part of the Recovery and Resilience Plan, stakeholders collaborated across sectors to explore the potential of insects as bioindustrial tools to address food system challenges. A structured, integrated approach combining health and sustainability considerations was matured and applied to pilot food products developed through this initiative. Recognising the potential health and sustainability impacts of these products, a comprehensive assessment was carried out. Results This study defined a structured, integrated approach to assessing the health and sustainability impacts of foods developed under the InsectERA agenda. Key steps included i) identifying critical issues and questions, ii) prioritising considerations, iii) defining methodologies, iv) collecting and analysing data, and v) integrating results for communication. Conclusions The study highlights the importance of integrated approaches in addressing food system transitions. Integrated approaches, guided by the One Health framework, play a critical role in informing policy decisions by providing policy makers with robust evidence. There is an urgent need for food system transformation based on decisions that holistically consider health and sustainability impacts, to ensure the protection of Public Health. Key messages • Integrating health and sustainability into the transition of food systems, within the One Health framework, is crucial for identifying options that safeguard Public Health. • A structured, integrated approach within a multi-stakeholder environment offers robust insights for policy decisions, advancing sustainable food systems.

Housing Inclusion Perspective: The Causal Structure of Housing Cost Burden, Fertility Intentions, and Social Housing in Urban China

To address low fertility and enhance urban inclusiveness and sustainability, this study conducted a questionnaire survey in 35 cities in China, systematically collected data on housing inclusiveness and fertility intentions, and used the SEM to analyze the causal relationship between housing costs burden, fertility intentions, and perceived need for social housing. The results show that the housing cost burden has a statistically significant positive (+) effect on the perceived need for social housing and a statistically significant negative (−) effect on fertility intentions, and that fertility intentions have a positive (+) effect on the perceived need for social housing. Notably, the direct effect of the housing cost burden on the perceived need for social housing (0.15) is greater than the total effect of the housing cost burden on the perceived need for social housing mediated by fertility intentions (0.14). This suggests that even when housing costs are high, families who still plan to have children exhibit a greater demand for social housing. Therefore, social housing can positively impact fertility intentions and help reduce housing cost pressures on families. Additionally, actively promoting inclusive housing development will have a significant impact on the sustainable growth of the urban population and economy, making meaningful contributions.

Health, an ageing labour force, and the economy: Does health moderate the relationship between population age-structure and economic growth?

Abstract Research often suggests that population ageing will be detrimental for the economy due to increased labour market exits and lost productivity, however the role of population health and disability at older ages is not well established. Identifying whether the health of older people affects economic outcomes is challenging due to methodological issues. Using country-level panel data, we estimate the relationship between the size of the older working age population (aged 55-69) and economic growth across 180 countries from 1990 to 2017. We run models using annual data and 5-year moving averages of real per capita GDP growth as dependent variables. This enables us to quantify the gains in real per capita GDP growth associated with a healthy older working-age population on a country-by-country basis. The initial models confirm an inverse-U or hump-shaped relationship between population age groups and economic growth. In the 5 year average GDP growth model, the coefficient for the inverse of YLDs among 55-69 year olds is positive and significant at p < 0.01. The interaction term is significant at p < 0.001 in the same model. Across all countries, a 5% improvement in YLDs is associated with at minimum 0.3% predicted additional annual real per capita GDP growth. While a larger share of the older working-age population at ages 55-69 has historically been associated with slower real per capita GDP growth, low levels of disability in this age group can reduce or even eliminate these adverse economic effects. We consistently find a significant positive interaction between disability and the share of the population at ages 55-69, suggesting that adverse economic effects are amenable to policy intervention.