Search Results (167)

Background/Objectives: Plant-based dietary patterns like the Dietary Approaches to Stop Hypertension (DASH) reduce cardiovascular risk, which is a leading cause of mortality globally and in Spain. Diet is also a major environmental determinant, highlighting the need to evaluate public health alongside environmental sustainability. The aim of this study was to analyze the evolution of adherence to the DASH dietary pattern in Spain between 2006 and 2023 and evaluate its relationship with environmental sustainability indicators. Methods: This was an ecological epidemiological study. Food consumption data were harmonized into daily servings to calculate annual DASH scores using a standard 80-point methodology. Environmental impact was assessed by calculating the comprehensive Ecological Footprint (EF) using the Agribalyse^® 3.2 database. The study utilized open data from the Spanish Household Budget Surveys, capturing the consumption habits of approximately 24,000 randomly selected Spanish households annually from 2006 to 2023. The primary measures evaluated were the annual DASH adherence index score and the overall environmental Ecological Footprint. Temporal trends were evaluated using segmented regression models selected via the Akaike Information Criterion and Davies test. Pareto analysis determined individual food group environmental contributions, and correlations assessed the relationship between DASH scores and the EF. Results: DASH adherence increased by 8.26% over the study period, peaking in 2020. The EF demonstrated an overall decrease over time, largely driven by reduced consumption of meat, fish, and eggs. A strong inverse correlation was found between the DASH score and the EF (r = −0.8237 (95% CI: −0.932 to −0.580; p < 0.001)). Conclusions: A shift toward the DASH dietary pattern in Spain demonstrates potentially convergent health and environmental associations, promoting population cardiovascular health potential while simultaneously mitigating environmental impacts. Full article

Household vulnerability assessment in Malaysia has traditionally relied on income-based indicators, which do not adequately capture multidimensional deprivation. To address this limitation, this study employs Random Tree–Dirichlet Process Mixture Model (RT-DPMM) to identify latent heterogeneity in spending patterns and their associated socioeconomic characteristics. Using microdata from Household Expenditure Survey (HES), this study performs clustering on 5130 stable household head samples with nine spending proportional features to model their joint distribution as mixtures of Dirichlet distributions, while five socioeconomic covariates inform cluster allocation through Random Tree embeddings. The proposed RT-DPMM identifies four distinct spending clusters: Balanced Budget Households (Cluster 1, N = 2883), Mobility and Home-Support Households (Cluster 2, N = 642), Basic Essentials-Focused Households (Cluster 3, N = 977), and Luxury Households (Cluster 4, N = 628). Cluster 1 and 3 are characterized as relatively vulnerable groups. These clusters have lower income levels and allocate a larger budget share in Food and Beverages, consistent with the Engel Law’s interpretation of higher food percentage in lower income households. Cluster 1 households primarily allocate their budget evenly across essential and non-essential spending. Cluster 3 are mostly elderly household heads with the highest budget shares in essential spending. In contrast, Cluster 2 and 4 appear relatively better off financially, given their higher income and larger spending share to non-essential categories. These findings suggest that social assistance policies should target expenditure patterns, rather than relying solely on income-based targeting. Full article

Community disaster resilience is increasingly guiding risk-reduction investments, but in many Southeast European settings, comparable subnational data remain scarce. This study assesses perceived community disaster resilience across Serbia by combining BRIC–DROP dimensions into a single index and analyzing differences across hazard types and sociodemographic factors. A cross-sectional household survey was conducted using multistage random sampling and the “next birthday” method for respondent selection. The final sample included 1200 adults from 22 local government units across four regions: Belgrade, Vojvodina, Šumadija & Western Serbia, and Southern & Eastern Serbia. Participants evaluated preventive measures and societal resilience for ten hazard types and considered five social dimensions: social structure, social capital, social mechanisms, social equity/diversity, and social beliefs. Descriptive statistics, bivariate analyses (including Pearson correlations, t-tests, and ANOVA), and multiple linear regression identified key predictors of preventive behavior and perceived resilience. Composite scores highlighted spatial resilience differences. Overall perceptions were generally low, mostly falling below the midpoint of the scale. Furthermore, the highest ratings for implemented preventive measures were recorded for pandemics/epidemics, storms/hail, and floods, whereas the lowest were observed for environmental pollution and droughts. Perceived resilience was highest for snowstorms, storms/hail, and pandemics/epidemics, and lowest for environmental pollution and droughts. Also, respondents reported relatively strong family ties and favorable perceptions of communication and access to basic supplies, but weak institutional capacity, particularly in budget allocation, early warning and public notification, rapid decision-making, and evacuation and shelter readiness. Regression results were statistically significant but explained only a small portion of the variance. Age and public-sector employment positively predicted perceived resilience; fear, income, and, to a lesser extent, education were negatively associated. These findings highlight the structural and psychosocial factors that shape perceptions of resilience. The BRIC–DROP composite indicates generally low perceived preparedness and resilience, especially in risk communication, evacuation and shelter readiness, and financing—the key bottlenecks in strengthening local resilience. The results recommend combining institutional reform with targeted risk communication to reduce fear and build trust, especially focusing on hazard areas with the lowest confidence, such as environmental pollution and drought. Full article

Background/Objectives: Micronutrient malnutrition, particularly deficiencies in calcium, vitamin D, iron, zinc, and iodine, remains a significant public health issue among school-aged children in Morocco. Processed cheese, such as “The Laughing Cow” (TLC), has potential as a vehicle for fortification due to its widespread consumption and accessibility. This study aimed to evaluate the impact of fortified TLC on micronutrient intake and adequacy relative to the Recommended Dietary Allowances (RDA), among Moroccan children aged 6–12 years, and to explore differences in effects by socioeconomic status (SES). Methods: Data from the Moroccan Household Budget Survey (2013–2014) included 9266 children (39.4% TLC consumers). Dietary intake was assessed using 24 h recalls, and nutrient composition was analyzed using Ciqual 2020 tables and specialized software. Fortification scenarios were modelled to estimate potential impacts on micronutrient intake and compliance with RDAs. Results: Under the modelling scenarios, consumption of one portion/day of fortified TLC significantly improved RDAs compliance for iron, iodine, and zinc (p < 0.05). There was also an increase in RDA compliance for calcium and vitamin D, but differences were not significant. The impact of fortification on micronutrient intake and RDA compliance increased with socioeconomic status. Consumers of more than one portion/day showed the highest compliance with RDAs (p < 0.001). Fortification effects were consistent across age subgroups. Conclusions: Fortifying processed cheese represents a feasible strategy to address micronutrient deficiencies among Moroccan schoolchildren. This study highlights the potential of targeted fortification programmes to improve public health outcomes, particularly in vulnerable populations. Further research is needed to optimize fortification approaches and ensure sustainability. Full article

This article uses two waves of panel data from China Land Economic Survey (CLES) in Jiangsu Province and employs a fixed-effects two-stage least squares (FE-2SLS) approach to identify pension effects on farmers’ labor allocation and land transfer decisions. In the FE-2SLS models, pension is instrumented by the average pension of other households in the same village. The results show that pension promotes land transfer-out, reduces household farm labor input, and increases household off-farm labor input. We further identify intra-household heterogeneity behind the pension effects. Specifically, pensioners in a household tend to leave farming activities without transitioning to off-farm employment, while non-pensioners shift the labor from farm to off-farm employment. We also examine heterogeneity by household budget pressure using two grouping strategies based on shortage experience and a composite budget-constraint indicator. The results show that the pension effects are more clearly observed among households without budget shortage. The estimates for households with budget shortage are less precise. These findings suggest that pension effects are complex in driving farmers’ resource allocation in their households. However, Jiangsu Province provides a substantial number of off-farm employment opportunities and features a well-developed land transfer market. The estimated pension effect in this area may not be applicable to less developed regions. Full article

The rapid growth of distributed energy resources (DERs) is transforming distribution networks and increasing the need for coordinated flexibility management to maintain secure and economically efficient operation. In this work, we examine how uncertainty in load demand and photovoltaic (PV) generation affects incentive-based flexibility coordination within a hierarchical three-level framework. The proposed architecture integrates household energy management systems (HEMSs), an aggregator responsible for incentive allocation, and a distribution system operator (DSO) model based on AC optimal power flow. To account for demand and PV variability, a $\mathrm{\Gamma }$-budget-robust optimization approach is adopted. Also, an incentive–penalty mechanism is introduced to allocate compensation according to each prosumer’s actual flexibility contribution while promoting economic fairness. The entire framework is implemented in PYOMO and tested on the IEEE 33-bus distribution system. A comparative evaluation between deterministic and uncertainty-aware cases is conducted to quantify the cost of robustness and to analyze its influence on flexibility participation, incentive distribution, household net cost, and voltage regulation performance. The results indicate that uncertainty can lead to deviations from initially scheduled flexibility commitments, thereby triggering penalty signals during re-optimization and strengthening contractual compliance. Although the robust formulation results in a moderate increase in operational cost, it substantially improves voltage compliance and overall system reliability. Overall, the findings highlight the importance of explicitly incorporating uncertainty in multi-level flexibility coordination to ensure both technical consistency and practical enforceability in modern distribution networks. Full article

Electric vehicle(EV) diffusion exhibits nonlinear, path-dependent dynamics shaped by interacting economic, technological, and social constraints. This paper develops a unified hybrid systems framework that captures these complexities by integrating microfounded household choice, capacity-constrained firm behavior, local network spillovers, and multi-level policy intervention within a Filippov differential-inclusion structure. Households face heterogeneous preferences, liquidity limits, and network-mediated moral and informational influences; firms invest irreversibly under learning-by-doing and profitability thresholds; and national and local governments implement distinct financial and infrastructure policies subject to budget constraints. The resulting aggregate adoption dynamics feature endogenous switching, sliding modes at economic bottlenecks, network-amplified tipping, and hysteresis arising from irreversible investment. We establish conditions for the existence of Filippov solutions, derive network-dependent tipping thresholds, characterize sliding regimes at capacity and liquidity constraints, and show how network structure magnifies hysteresis and shapes the effectiveness of local versus national policy. Optimal-control analysis further demonstrates that national subsidies follow bang–bang patterns and that network-targeted local interventions minimize the fiscal cost of achieving regional tipping. Beyond theoretical characterization, the framework is structurally calibrated to match the order-of-magnitude effects reported in leading empirical and simulation-based studies, including network diffusion models, agent-based simulations, bass-type specifications, and fuel-price shock analyses. The hybrid formulation reproduces short-run percentage-point subsidy effects, long-run forecast dispersion under alternative network assumptions, and policy-induced equilibrium shifts observed in the applied literature while providing a unified geometric interpretation of these heterogeneous results through explicit basin boundaries and regime switching. The framework provides a complex systems perspective on sustainable mobility transitions and clarifies why identical national policies can generate asynchronous regional outcomes. These results offer theoretical foundations for designing coordinated, cost-effective, and network-aware EV transition strategies. Full article

Neighbourhood-scale improvements in building energy efficiency face intertwined challenges of retrofit adoption, distributional equity, and resilience to energy price shocks. While existing studies often examine individual policy instruments in isolation, how governance tools jointly shape diffusion dynamics, social sustainability, and fiscal feasibility remains insufficiently understood. This paper develops an agent-based model of a heterogeneous urban neighbourhood to examine how four governance instruments—incentives, feedback, participation, and compliance—interact to influence household retrofit adoption, emissions, energy burden outcomes, and public budget exposure. Outcomes are evaluated using an ESG-informed indicator structure: E captures aggregate neighbourhood emissions; S captures household energy burden (level, overburden prevalence, and inequality); and G captures governance feasibility (adoption/compliance dynamics and cumulative net public cost, defined as administration + subsidies + enforcement minus fine revenues). An exogenous energy price shock is introduced to assess social resilience using burden peaks, overshoots, recovery time, and post-shock volatility. The simulation results show that participation-based mechanisms generate rapid early diffusion and higher endpoint adoption, with correspondingly earlier and larger emission reductions; in the baseline runs, the incentive–participation mix (I+P) attains the highest endpoint adoption and the lowest endpoint emissions. Incentives and feedback yield more gradual diffusion and moderate improvements, while compliance reduces voluntary uptake but delivers partial emission reductions through enforcement and can generate net fiscal revenue under the accounting definition when fine revenues exceed enforcement outlays. Participation-centred mixes tend to lower the average burden trajectories and exhibit modestly smaller shock-induced peaks and overshoots, whereas inequality outcomes are more trade-off dependent: compliance-based enforcement can compress burden dispersion even with limited voluntary adoption, and adding compliance to participation primarily shifts performance toward lower inequality at higher net fiscal exposure. These findings suggest that neighbourhood-scale building energy governance depends on matching policy mixes to diffusion mechanisms, distributional objectives, and fiscal constraints. Full article

Household food expenditure reflects not only income differences, but also how demographic, economic, and institutional factors interact within the household. This study examines household food expenditure in Türkiye from a systems perspective, with a particular focus on the role of gender in shaping economic vulnerability. Using microdata from the 2018 Household Budget Survey, the analysis employs a two-stage framework that combines Artificial Neural Networks and a Tree-Augmented Bayesian Network. In the first stage, non-linear relationships among household characteristics are identified and the most influential determinants of food expenditure shares are determined. In the second stage, a probabilistic system model is constructed to conduct counterfactual “what-if” simulations. The results show that household food expenditure emerges as a systemic outcome influenced by income, education, employment stability, savings capacity, and asset ownership, with gender playing a central role. Female-headed households—particularly those living alone and facing limited education and unstable employment—have a substantially higher probability of allocating a large share of their budget to food. These findings are consistent with Engel’s law and highlight the gendered nature of economic vulnerability. The study suggests that food security policies should address employment stability, human capital, and access to productive assets alongside income support. Full article

The main aim of this study was to determine the share of Polish household income allocated to energy, taking into account socioeconomic diversity and income quintile distribution, as well as to identify changes in the burden of energy expenditures on budgets. The importance of this topic stems from the energy transformation of the European Union and the significant increase in energy prices in recent years, which may exacerbate existing energy poverty in Poland. The study utilized numerical data on household budgets published within Polish public statistics. The following measures were used: mean, quintiles, structure indicators, and fixed- and chain-based indices, as well as the relationship between income and expenditure (correlation coefficients). The research was conducted using data from 2014–2022 or selected years within this period. The highest share of energy expenditures in total expenditures was recorded among households of annuitants and farmers. However, annuitant households have the lowest incomes and are most vulnerable to energy poverty. The disparity in energy expenditure between the wealthiest and poorest households has narrowed. Educational efforts on energy efficiency in households should therefore continue, alongside the development of support mechanisms for those with the lowest incomes. Full article

Background/Objectives: Sugar-sweetened beverage (SSB) consumption has been linked to obesity, metabolic diseases, and rising healthcare costs. This study aimed to assess the impact of a 20% excise tax on SSBs in Brazil on obesity/overweight prevalence, seven musculoskeletal and cardiovascular diseases, and related healthcare costs, with their associated impacts on health inequalities. Methods: Using 2017/2018 Brazilian Household Budget Survey data for baseline consumption and own- and cross-price elasticities for taxed beverages, we estimated changes in caloric consumption for the entire population and for lower- and upper-income quartiles. The PRIMEtime dynamic individual-level simulation model projected body weight changes, lifetime Quality-Adjusted Life-Years (QALYs), healthcare costs (discounted at 5%), and disease cases (20-year horizon). Results: A 20% excise SSB tax was projected to reduce obesity prevalence by 1.7 percentage points in men and 1.5 percentage points in women, from baseline rates of 19.8% and 23.6%, respectively. Lifetime gains were estimated at 17,878 QALYs per million men and 12,181 per million women, alongside healthcare cost savings of Int$520 million. Impacts varied by income, with smaller health gains in the lowest quartile and higher among the wealthiest. Over 20 years, the tax could avert 1784 cases of type 2 diabetes mellitus/100,000 adults (52% in men) and 1070 cases of ischemic heart disease/100,000 adults (80% in men). Conclusions: A 20% excise SSB tax in Brazil could yield large health and cost benefits. With the recent approval of the Selective Tax under Complementary Law 214/2025, Brazil has a timely opportunity to translate these projected benefits into effective public health policy. Full article

Ensuring affordable and reliable electricity access to areas with low population density is challenging, as network sparsity and lower connectivity rates can make it nearly impossible for electric utilities to cover the cost of interconnection without raising electricity tariffs. Utility providers that consider extending their networks to remote households must balance multiple and often conflicting objectives, including investment cost, grid resilience, geographical coverage, and environmental impacts. In this paper, a multi-objective decision-making framework is proposed for the electrification of rural households, considering traditional distribution network extension as well as microgrid deployment. In order to condense a wide range of spatial inputs into a tractable problem, a multi-criteria decision-making approach is adopted to identify and rank candidate sites for microgrid deployment that offer superior performance over a variety of technical, environmental, and economic criteria. A novel optimization model is then proposed using multi-objective Chebyshev goal programming, in which project costs, environmental impacts, and energy justice criteria are jointly optimized. The applicability of this framework is demonstrated through a case study of the Shiprock region within the Navajo Nation. The results indicate that the proposed methodology provides a balanced trade-off among conflicting objectives and identifies a priority order of loads to energize first under marginally increasing budgets. Full article

Background/Objectives: Dietary patterns have changed over time, characterising a process of nutritional transition that reflects socioeconomic and demographic inequalities among different populations. This study assessed changes in dietary consumption patterns and the associated social determinants, comparing two time periods in a sample of individuals from a state in the Northeast Region of Brazil. Methods: Data from the 2008–2009 and 2017–2018 Household Budget Survey for the state of Paraíba were analysed, totalling 951 and 1456 individuals, respectively. Foods were categorised according to the NOVA classification and compared based on sociodemographic and economic variables. To determine the factors that most strongly explain the contribution of each NOVA food group to the diet, beta regression analysis was conducted. Results: Differences were observed between the two periods regarding the dietary contribution of the NOVA food groups, with a decrease in consumption of unprocessed foods and an increase in ultra-processed foods. Living in urban areas, being an adolescent, and having an income above the minimum wage were associated with reduced intake of unprocessed foods in both periods. Additionally, being an adolescent and having more than eight years of schooling were associated with higher consumption of ultra-processed foods. Conclusions: The population under study showed changes in food consumption, reflecting a transition process that is occurring unevenly across socioeconomic and demographic groups, thereby reinforcing social inequalities. These findings can guide priorities in food and nutrition policies, highlighting the need for intervention studies to evaluate the effectiveness of such actions. Full article

Non-agricultural business activity of farmers is crucial not only for stabilizing farm income but also for the multifunctional development of rural areas. Capturing changes in the level and nature of this activity supports the development of sustainable agricultural and rural policy. In this context, this study aimed to identify the scale and types of non-agricultural business activity and to recognize the main determinants of such business activities undertaken by farmers in Poland between 2002 and 2022. Sectoral-level data from the Agricultural Censuses and cyclical studies of the structure of farms and household budgets were used to approximate underlying motivations for running non-agricultural business (opportunity vs. necessity entrepreneurship). The findings indicate that, in Poland, the impact of regressive factors remains strong, pushing farmers to take on additional business activity due to the large share of small and very small farms. However, during the 21st century, a gradual spread of opportunity entrepreneurship among Polish farmers has been observed. This study highlights the rationale for supporting non-agriculture business activity motivated by progressive factors to increase the income resilience of farmer households and the sustainable development of agriculture. The article indicates the need for further research on the motives for undertaking non-agricultural economic activities by farmers and the impact of this activity on the allocation of farm resources. Full article

Background/Objectives: Recruiting and retaining low-income participants in community-based diabetes interventions remains a persistent challenge, particularly in medically underserved areas. This study describes engagement strategies and lessons learned recruiting for a 12-month pilot of a community-based, medically tailored nutrition program for diabetes remission and weight loss. Methods: A descriptive, exploratory mixed-methods study was performed to assess the effectiveness of recruitment and engagement strategies in the HEAL Diabetes program and identify areas for improvement. Recruitment and enrollment data were tracked utilizing recruitment logs and field notes. Descriptive statistics were used to analyze recruitment activity and retention rates, while qualitative analysis of fieldnotes identified key barriers and facilitators. Results: Among 83 eligible participants, 63 (75.9%) completed the in-person screening and 35 (55.6% enrollment rate) enrolled. Retention was high, with 30 completing the study. Participants were largely African American (97.1%), female (70.6%), average age of 59.8 years, with a household income below USD 49,000 (74.3%). Recruitment cycles achieved 87.5% of the target before budget constraints halted enrollment. Recruitment was hindered by limited clinical integration, social barriers and life demands, while facilitators to recruiting included trust, flexibility, and tangible support for participation. Conclusions: Conventional recruitment methods, including registry-based approaches, were insufficient for engaging underserved populations. Participant-centric strategies, emphasizing trust, practical support, and structural and cultural relevance, can help enhance enrollment and retention. Effective engagement in community-based diabetes interventions requires multifaceted approaches that address clinical, social, and structural barriers to participation. Full article