Impact Of Changes Research Articles

MENTAL HEALTH IN THE CONTEXT OF CLIMATE CHANGE

Climate change has intensified in recent decades, generating devastating consequences for the environment and, consequently, for human health. Mental health has emerged as a critical area of concern, since extreme weather events such as natural disasters, droughts and floods directly impact the psychological well-being of vulnerable populations. This study aims to analyze how climate change influences mental health, focusing on the psychological effects these changes have on communities in situations of vulnerability. The aim of this analysis is to explore how climate change impacts the mental health of vulnerable populations, discussing the main risk factors involved and addressing strategies that can be adopted to minimize these effects. This discussion is relevant because recognizing the emotional consequences of the climate crisis creates a basis for developing public health practices and psychosocial approaches that promote resilience and adaptation. By focusing on the psychological impact of climate change, we aim to contribute to a more comprehensive and inclusive response to the challenges of a changing world. This is a literature review, based on a qualitative approach, using the Scielo, Google Scholar and PubMed databases. To enhance the research, the health descriptors “climate change”, “mental health”, “psychological impacts” and “solastalgia” were used, with a time frame between 2007 and 2020. The methodology adopted for this analysis consists of a comprehensive literature review, using academic sources and reports from health and environmental organizations. The study addresses how extreme weather events, food insecurity and forced displacement affect mental health, leading to an increase in disorders such as anxiety, depression and post-traumatic stress disorder (PTSD). In addition, the social inequalities that aggravate these impacts are discussed, considering that populations with less access to health resources and services are more susceptible to the adverse effects of climate change. It is concluded that climate change poses a significant threat to mental health, especially for vulnerable populations already facing socio-economic challenges. It is essential that public health policies integrate mental health considerations into climate change adaptation and mitigation strategies. Promoting psychological support programs and implementing targeted interventions can help minimize the negative impacts on mental health, strengthening the resilience of affected communities and promoting a more effective response to climate crises.

Advanced Biofuel Value Chains Sourced by New Cropping Systems With Low iLUC Risk

ABSTRACTIncreasing lignocellulosic feedstock for advanced biofuels can tackle the decarbonization of the transport sector. Dedicated biomass produced alongside food systems with low indirect land use change (iLUC) impact can broaden the feedstock availability, thus streamlining the supply chains. The objective of this study was the design and evaluation of advanced ethanol value chains for the Emilia‐Romagna region based on low iLUC feedstock. Two dedicated lignocellulosic crops (biomass sorghum and sunn hemp) were evaluated in double cropping systems alongside food crop residues (corn stover and wheat straw) as sources to simulate the value chains. A parcel‐level regional analysis was carried out, then the LocaGIStics2.0 model was used for the spatial design and review of the biomass delivery chain options regarding cost and greenhouse gas (GHG) emissions of the different feedstock mixes. Literature data on bioethanol production from similar feedstocks were used to estimate yields, process costs, and GHG emissions of a biorefinery process based on these biomasses. Within the chain options, GHG emissions were overly sensitive to cultivation input, mostly N‐fertilization. This considered, GHG emissions resulted similar across different feedstock with straw/stover (averaging 13 g CO2eq MJ−1 fuel), sunn hemp (14 g CO2eq MJ−1 fuel), and biomass sorghum (16 g CO2eq MJ−1 fuel). On the other hand, the bioethanol produced from biomass sorghum (608 € Mg−1 of bioethanol) was cheaper compared with straw (632 € Mg−1), sunn hemp (672 € Mg−1), and stover (710 € Mg−1). The bioethanol cost ranged from 0.0017 to 0.020 € MJ−1 fuel depending on the feedstock, with operations and maintenance impacting up to 90% of the final cost. In summary, a single bioethanol plant with an annual capacity of 250,000 Mg of biomass could replace from 5% to 7% of the Emilia‐Romagna's ethanol fuel consumption, depending on the applied sourcing scenario.

A Novel Input Schematization Method for Coastal Flooding Early Warning Systems Incorporating Climate Change Impacts

Coastal flooding poses a significant threat to coastal communities, adversely affecting both safety and economic stability. This threat is exacerbated by factors such as sea level rise, rapid urbanization, and inadequate coastal infrastructure, as noted in recent climate change reports. Early warning systems (EWSs) have proven to be effective tools in coastal planning and management, offering a high cost-to-benefit ratio. Recent advancements have integrated operational numerical models with machine learning techniques to develop near-real-time EWSs, leveraging data obtained from reputable databases that provide reliable hourly sea-state and sea level data. Despite these advancements, a stepwise methodology for selecting representative events, akin to wave input reduction methods used in morphological modeling, remains undeveloped. Moreover, existing methodologies often overlook the significance of compound extreme events and their potential increased occurrence under climate change projections. This research addresses these gaps by introducing a novel input schematization method that combines efficient hydrodynamic modeling with clustering algorithms. The proposed methodοlogy, implemented in the coastal area of Pyrgos, Greece, aims to select an optimal number of representative sea-state and water level combinations to develop accurate EWSs for coastal flooding risk prediction. A key innovation of this methodology is the incorporation of weights in the clustering algorithm to ensure adequate representation of extreme compound events, also taking into account projections for future climate scenarios. This approach aims to enhance the accuracy and reliability of coastal flooding EWSs, ultimately improving the resilience of coastal communities against imminent flooding threats.

Climate Change Impacts on Agricultural Systems Mitigation and Adaptation Strategies: A Review

Climate change poses a substantial threat to global agricultural systems, impacting crop yields, livestock productivity, and resource availability through rising temperatures, altered precipitation patterns, and increased frequency of extreme weather events. This review synthesizes current understanding of climate change impacts on agriculture and explores strategies for mitigating greenhouse gas (GHG) emissions while enhancing system resilience through adaptation. Mitigation approaches, such as conservation agriculture, agroforestry, and improved nutrient and livestock management, show significant potential to reduce emissions and increase carbon sequestration. However, economic, technological, and institutional barriers such as high implementation costs, limited access to finance, and inadequate policy support restrict their adoption. Adaptation strategies, including crop diversification, advanced water management, and climate-resilient technologies, are critical for sustaining agricultural productivity in variable climates. Synergies between mitigation and adaptation, such as integrating trees into croplands, can provide co-benefits, but trade-offs arise when resource competition occurs or land is diverted from food production to carbon sequestration. The review highlights the need for interdisciplinary research, robust data infrastructure, and tailored policies to bridge knowledge and resource gaps, particularly in vulnerable regions. Successful implementation requires coordinated efforts across stakeholders, supported by enabling policy frameworks that incentivize sustainable practices and align with global climate goals. Future research should prioritize understanding the long-term impacts of integrated strategies, enhancing monitoring systems, and fostering inclusive approaches that consider local contexts and socio-economic conditions. Addressing these challenges holistically will be crucial to building resilient agricultural systems capable of maintaining food security and supporting livelihoods in the face of accelerating climate change.

Determining the Relationship Between Corneal Stiffening and Tissue Dehydration After Corneal Cross-Linking.

To quantify corneal cross-linking (CXL)-induced stiffening via mechanical testing to estimate the impact of changes in hydration levels (H) and evaluate depth-dependent tissue hydration after CXL. Eighty-three porcine corneal buttons were divided into three groups: Standard protocol CXL (S-CXL), accelerated CXL (A-CXL), and untreated (nonirradiated riboflavin-only) controls. Samples were hydrated or dehydrated to modulate H and dynamic mechanical analyzer compression tests were performed to measure Young's modulus (E). To extract the solid tissue network modulus, the cornea was modeled as a biphasic material after measuring E at different H. Corneal hydration was correlated with depth-dependent tissue thickness characterized by confocal reflection microscopy (CRM). Young's modulus increased fourfold after S-CXL (0.72 ± 0.1 MPa) and threefold after A-CXL E (0.53 ± 0.12 MPa) versus controls (0.17 ± 0.045 MPa). However, H decreased from 4.07 ± 0.35 in controls to 2.06 ± 0.2 after S-CXL and 2.79 ± 0.12 after A-CXL. After H modulation and biphasic mechanical modeling, Young's modulus for corneal solid tissue network showed only a 1.8-fold increase after S-CXL (2.25 MPa) and 1.5-fold increase after A-CXL (1.85 MPa) versus controls (1.22 MPa). With CRM, the overall thickness of the corneal tissue was found to linearly correlate to hydration H as expected. No appreciable depth dependence of hydration-induced thickness changes throughout the corneal buttons were observed. Corneal tissue hydration changes significantly impact measured corneal stiffness after CXL using mechanical testing. Not considering H leads to major overestimation of the stiffening effect of the CXL procedure. Depth-dependence of corneal thickness because of changing hydration is strongly dependent on the integrity of the tissue.

Corporate environmental R&D: does organisational innovation matter?

ABSTRACT Investments in environmental research and development (R&D) are a crucial element for firms to make superior environmental performance compatible with financial performance. This relevance of environmental R&D suggests a need to identify its drivers. However, the literature on environmental R&D has given a prominent focus to external drivers to the firm, with a limited focus on factors internal to the firm. In contrast, the impact of crucial organisational changes in firms, in the form of organisational innovation, has not been addressed. We argue that organisational innovation drives environmental R&D expenditures. Using data on manufacturing firms from the Spanish Technological Innovation Panel survey during 2008–2016, we find support for this idea. Further analysis suggests that it is particularly the introduction of new methods of organising workplaces that is positively associated with environmental R&D. This suggests that a regulatory environment that facilitates workplace flexibility may promote environmental R&D investments.

Assessing the impact of climate change by using Mann–Kendall, Pettitt and statistical downscaling model (case study: Tabriz station)

Assessing the impact of climate change by using Mann–Kendall, Pettitt and statistical downscaling model (case study: Tabriz station)

Warming Leads to Lower Rice Quality in East Asia

AbstractRice quality, which is intricately connected to market value and human nutrition, is sensitive to weather conditions. However, the relative importance of the different climatic factors is poorly understood, and the impact of climate change on rice quality has been little studied on a large scale. Here, using more than 35 years of rice quality data, we present the first effort to determine the key climate variables driving rice quality in China and Japan. Results show a significant decline in high quality rice rate (HRR, an indicator of rice quality), mainly driven by warm nighttime temperatures when they exceed a critical threshold estimated at 18°C and 12°C in China and Japan, respectively. Climate projections suggest a continuing decreasing trend in HRR under moderate and high emission scenarios by 2100. These findings emphasize the importance of breeding new heat tolerant cultivars to maintain stable rice quality in the future.

Analyzing the Distribution Patterns of Endemic Quercus vulcanica (Boiss. et Heldr. ex) Kotschy in Türkiye Under Climate Change Using Ensemble Modeling

Quercus vulcanica (Boiss. et Heldr. ex) Kotschy (Kasnak oak), one of the 18 Quercus species naturally distributed in Anatolia, is an endemic species with a restricted distribution range. In accordance with the International Union for the Conservation of Nature (IUCN) Red List of Endangered Species classification, Quercus vulcanica is designated as a species of low risk (LC: Least Concern). However, it is predicted that the habitat of Quercus vulcanica will narrow and that the species will become endangered as a result of potential climate change scenarios in the future. The aim of this study was to estimate the temporal and spatial distribution of Quercus vulcanica in Anatolia during the LGM, as well as to examine the impact of present and future climate changes on the species. In this context, principal component analysis was applied to 19 bioclimatic variables of the Community Climate System Model Version 4 (CCSM4) climate model, with nine variables identified for use in modeling. Habitat suitability was estimated using the Biodiversity Modeling (BIOMOD) ensemble modeling method, which combines the results of nine different algorithms through the R package ‘biomod2’, applying both committee averaging and weighted average approaches. To evaluate the performance of the models, the Area Under the Curve (AUC) of Receiver Operating Characteristics (ROC), True Skill Statistics (TSS), KAPPA and Boyce Index were calculated. The contributions of the environmental variables were determined on a per-algorithm-model basis. The results of the analyses show that the bioclimatic variables that contribute the most to the distribution of the species are Bio8. The modeling results show that Quercus vulcanica is capable of occupying suitable habitat areas across the majority of Anatolia during the Last Glacial Maximum (LGM). It is anticipated that future projections will indicate a notable reduction in the extent of suitable habitat for the species, with the remaining areas confined to the vicinity of the Ilgaz Mountains, Köroğlu Mountains and Bolkar Mountains. Given the increasing destruction that Quercus vulcanica, an endemic plant, will be adversely affected by as a result of human impacts and climate change, it is of the highest importance to develop adaptation strategies with a view to protecting the species’ habitat and the sustainability of the species.

To Investigate the Impact of Land Use Change on the Potential Groundwater Recharge on Hillslope With Deep Loess Deposits

ABSTRACTAccurately estimating groundwater recharge in hilly areas with limited water and thick vadose zones is challenging. This study investigated the impact of land use changes on groundwater recharge at a hillslope scale of Yuanzegou Watershed in China's Loess Plateau. Three adjacent hillslopes were selected for three different land uses: arbor (jujube, Ziziphus jujuba Mill.), subshrub (native grass, Artemisia gmelinii), and crop (millet, Setaria italica). Soil cores (as deep as 10–16/18 m) were collected at each of the three landscape positions on a hillslope. Reported tritium profiles in the watershed were used to estimate the net chloride input into vadose zone on hillslope associated with inverse chloride mass balance (CMB) method/chloride accumulation method (CAM). Soil water content and chloride profiles in the study were measured to determine recharge rates at each landscape position beneath different vegetation types. For the first time, we evaluated the actual chloride input into vadose zone on hillslopes as 540.2 ± 23.8 mg m−2 yr.−1, excluding the impact of runoff. Then, estimated recharge rates ranged from 42.7 ± 3.5 to 62.4 ± 4.7 mm yr.−1, consistent with nearby studies. Results showed that groundwater recharge does not change with landscape position except for higher value on upslope beneath subshrub hillslope. In contrast, groundwater recharge did significantly reduce by 12.9% ± 5.4% and 26.5% ± 4.5% after conversion from cropland to subshrub/arbor on the hillslope, respectively. Our findings contribute to understanding the ecohydrological effects of land use changes on groundwater recharge on hillslope and help to select suitable afforested vegetation for greening efforts in water‐limited hilly areas, with a priority on groundwater safety.

Climate‐driven shifts in plant–soil feedback of a perennial grass species

Abstract Plant–soil feedback (PSF) plays a key role in determining the composition of plant communities, and understanding the impact of the ongoing climate change on PSF is thus crucial for predicting the consequences of climate change for ecosystems. Here, we conducted a growth‐chamber experiment to examine possible climate‐driven shifts in PSF of a perennial grass, Festuca rubra, originating from two climatically distinct sites, by using all factorial combinations of soil biota origin, plant origin, and cultivation climate. Soil biota generated more negative PSF effects when grown under the climatic conditions of their origin. This observation suggests that soil biota, especially soil pathogens, are well adapted to their local climate, exhibiting greater efficiency in suppressing plant growth within their climatic conditions. All plants, regardless of their origin, exhibited less negative PSF (expressed as relative performance in live vs. sterilized soil) when grown under warmer climate than under colder climate, likely due to positive effects of increased activity of soil decomposers and enhanced nutrient cycling. Plants showed negative PSF when grown with local soil biota under home climate, and the negative PSF disappeared when plants were grown with foreign biota or in away climates. This suggests that any disruption of the established plant‐soil‐climate interactions may lead to the release of plants from negative PSF, potentially destabilizing plant communities. Synthesis. Our results highlight the adaptions of soil biota to their native climate as key drivers of plant–soil feedback interactions and suggest that climate change could significantly alter these interactions, potentially leading to new plant community dynamics. These findings emphasize the need for further investigations to unravel the mechanisms driving these responses and evaluate their consequences for ecosystem resilience in the face of climate change.

Psychosocial Complaints and Life Satisfaction Among Greek University Students: A Pre- and Pandemic-Era Comparison

This study aims to identify and compare the prevalence and risk factors associated with psychosocial and psychological complaints, as well as life and study satisfaction, among Greek undergraduate students before and during the COVID-19 pandemic. Data were collected in two phases: initially, from 2018 to 2019 (pre-COVID), through face-to-face surveys, and later, from October 2020 to June 2021 (COVID period), through online surveys. The study, conducted at Democritus University of Thrace (DUTH) in Greece, utilized a repeated descriptive and comparative cross-sectional design. The sample comprised 540 and 641 undergraduate students during the pre-COVID and COVID period, respectively. The following questionnaires were used: I. A socio-demographic characteristics form, II. Psychosocial Complaints List (PCL), and III. Satisfaction with Life and Studies Scale (SLSS). During the COVID period, there was an increase of 63% in psychosocial complaints (p < 0.001), as indicated by the PCL total, and a 25% decrease in satisfaction with life and studies (p = 0.001), according to the SLSS, compared to the pre-COVID period. Incidences of “suicidal thoughts”, “sexual problems”, and “extreme psychological distress” nearly doubled (61%, 67%, and 104%, respectively) during the pandemic. Females exhibited a 33% increase in the PCL total during the COVID period compared to males (p < 0.001). These findings highlight the profound impact of pandemic-induced changes on students’ mental health and quality of life. Female gender and the pandemic period itself emerged as significant factors influencing these outcomes. Universities should prioritize the development of comprehensive support services to mitigate these adverse effects.

Dependence of cyanobacterium growth and Mars-specific photobioreactor mass on total pressure, pN2 and pCO2

In situ resource utilization systems based on cyanobacteria could support the sustainability of crewed missions to Mars. However, their resource-efficiency will depend on the extent to which gases from the Martian atmosphere must be processed to support cyanobacterial growth. The main purpose of the present work is to help assess this extent. We therefore start with investigating the impact of changes in atmospheric conditions on the photoautotrophic, diazotrophic growth of the cyanobacterium Anabaena sp. PCC 7938. We show that lowering atmospheric pressure from 1 bar down to 80 hPa, without changing the partial pressures of metabolizable gases, does not reduce growth rates. We also provide equations, analogous to Monod’s, that describe the dependence of growth rates on the partial pressures of CO2 and N2. We then outline the relationships between atmospheric pressure and composition, the minimal mass of a photobioreactor’s outer walls (which is dependent on the inner-outer pressure difference), and growth rates. Relying on these relationships, we demonstrate that the structural mass of a photobioreactor can be decreased – without affecting cyanobacterial productivity – by reducing the inner gas pressure. We argue, however, that this reduction would be small next to the equivalent system mass of the cultivation system. A greater impact on resource-efficiency could come from the selection of atmospheric conditions which minimize gas processing requirements while adequately supporting cyanobacterial growth. The data and equations we provide can help identify these conditions.

Impact of Site Conditions on Quercus robur and Quercus petraea Growth and Distribution Under Global Climate Change

Climate change has significant natural and economic implications, but its extent is particularly challenging to assess in forest management, a field which combines both of the previous aspects and requires the evaluation of the impact of climate change on tree species over a 100-year timeframe. Oaks are among the tree species of significant natural and economic value in Europe. Therefore, the aim of this study was to analyze all oak stands in Poland and verify the hypothesis regarding differences between Quercus robur and Quercus petraea stands in terms of soil type, annual total precipitation, average annual air temperature, and the length of the growing season. Additionally, this study aimed to analyze the impact of these differences on the growth rates of both oak species and test whether climate change may affect oak stands. A database containing 195,241 tree stands, including different oak species with varying shares in the stand (from 10% to 100%), was analyzed. A particular emphasis was placed on Q. robur and Q. petraea. The results show that, although both oak species have a wide common range of occurrence, there are clear differences in their habitat preferences. Based on the ordinal regression analysis of selected oak stands, it was concluded that an increase in air temperature of 1 °C could impair the growth of Q. robur and slightly improve the growth of Q. petraea. This may indicate the possibility of expanding the geographic range of sessile oaks towards the east and northeast under warming climatic conditions, provided that appropriate moisture conditions are maintained.

The Impact of Climate Change and Urbanization on Compound Flood Risks in Coastal Areas: A Comprehensive Review of Methods

Many cities worldwide are increasingly threatened by compound floods resulting from the interaction of multiple flood drivers. Simultaneously, rapid urbanization in coastal areas, which increases the proportion of impervious surfaces, has made the mechanisms and simulation methods of compound flood disasters more complex. This study employs a comprehensive literature review to analyze 64 articles on compound flood risk under climate change from the Web of Science Core Collection from 2014 to 2024. The review identifies methods for quantifying the impact of climate change factors such as sea level rise, storm surges, and extreme rainfall, as well as urbanization factors like land subsidence, impervious surfaces, and drainage systems on compound floods. Four commonly used quantitative methods for studying compound floods are discussed: statistical models, numerical models, machine learning models, and coupled models. Due to the complex structure and high computational demand of three-dimensional joint probability statistical models, along with the increasing number of flood drivers complicating the grid interfaces and frameworks for coupling different numerical models, most current research focuses on the superposition of two disaster-causing factors. The joint impact of three or more climate change-driving factors on compound flood disasters is emerging as a significant future research trend. Furthermore, urbanization factors are often overlooked in compound flood studies and should be considered when establishing models. Future research should focus on exploring coupled numerical models, statistical models, and machine learning models to better simulate, predict, and understand the mechanisms, evolution processes, and disaster ranges of compound floods under climate change.

A Study on Future Population Dynamics of Indigenous Earthworm Species in Golaghat District of Assam, India

This study presents a pioneering exploration into the population dynamics of indigenous earthworm species in the Golaghat district of Assam, India, through the lens of mathematical modeling. Recognizing the integral role of earthworms in enhancing soil productivity and ecosystem health, we embarked on a detailed longitudinal analysis spanning from 2018 to 2023 to assess their population trends across different seasons and subdivisions within the district. Utilizing the principles of Mathematical Biology, we employed the Malthus Growth model and the Logistic Growth model to estimate future population trajectories of earthworm species, integrating biological insights with mathematical rigor. Our methodology, combining extensive field data collection with sophisticated mathematical modeling, provides a replicable framework for similar ecological studies. This study contributes to the growing field of Mathematical Biology, offering a novel approach to understanding the complex interactions within ecosystems and the impact of environmental changes on key species. The outcomes offer valuable insights into sustainable agricultural practices and biodiversity conservation in tropical and subtropical regions, emphasizing the critical role of indigenous earthworm species in maintaining soil health and ecosystem services. Our findings reveal significant seasonal variations and highlight the resilience of these species in the face of ecological changes. The models suggest distinct population growth patterns, with the Logistic model providing a more realistic projection considering environmental constraints and resource availability. The bifurcation diagram is drawn for the Logistic map that presents the phenomena inside the chaotic region.

Natural Hazards and Climate Change Impacts on Food Security and Rural–Urban Livelihoods in Mozambique—A Bibliometric Analysis and Framework

Mozambique is confronted with numerous risks related to food security and natural disasters. The study conducted a literature review on natural hazards and food security. This can help to identify gaps and further areas of research. A bibliometric analysis was conducted using standardized text search terms, and the VOSviewer tool was used to analyze over 7000 scientific articles and cluster over 60,000 keyword co-occurrences. The results show that research on natural hazards for food security needs to be integrated. The priority topic of disasters focuses on specific hazards such as climate change, floods, and hurricanes, which are also linked to demographic and other social variables. More studies on food security, such as droughts, sustainable development, and other human and social conditions, are being conducted. Resilience as an emerging research paradigm needs to be addressed in comparison. One result is an analytical framework on impacts on food security in the context of disaster risk, based on the empirical findings of the literature review. It shows how everyday risks such as disease or food security can be conceptually better linked to natural hazards and resilience. It shows that further research is needed on the interlinkages of multiple risks, of which Mozambique is an outstanding example. The methodology presented is also applied to provide a framework for linking multiple risks to food security and natural hazards. The innovative dimension of the research is that this inquiry constitutes one of the pioneering attempts to conduct a bibliometric analysis of the linkages between natural hazards, food security, and resilience in Mozambique. Another noteworthy contribution is introducing a novel analytical framework that integrates food security and disaster risks.

Predicting the Impact of Climate Change on Corylus Species Distribution in China: Integrating Climatic, Topographic, and Anthropogenic Factors.

This study investigates the impact of climate change on the distribution of Corylus species in China using the MaxEnt model. Key environmental variables, such as Bio6 (mean temperature of the coldest month) and human footprint, emerged as significant determinants of habitat suitability. The study reveals substantial shifts in suitable habitats due to global warming and increased precipitation, with notable expansion towards higher latitudes. Species like Corylus heterophylla Fisch. ex Bess. and Corylus mandshurica Maxim. demonstrate resilience in extreme conditions, highlighting the importance of specific ecological traits for conservation. Future projections under various SSP scenarios predict continued habitat expansion, emphasizing the need for targeted conservation strategies to address the critical role of human activities. This research highlights the complex interplay between climatic, topographic, and anthropogenic factors in shaping Corylus habitats, advocating for integrated adaptive management approaches to ensure their sustainability amid ongoing climate change.

Process Mining on National Health Care Data for the Discovery of Patient Journeys of Older Adults

ObjectiveUnderstanding the longitudinal patterns of health care utilization among older adults is crucial for designing effective patient journeys and enhancing care coordination across settings. This study aims to uncover the most common patient journeys of older adults. DesignThis explorative study used process mining techniques to analyze national health care data from 2017 to 2019, focusing on patient care journeys of older adults (aged ≥65 years) in the Netherlands. Setting and ParticipantsData were sourced from Statistics Netherlands, encompassing all residents aged ≥65 years as of January 1, 2017. Health care usage declarations from various care settings during 2017-2019 were included. Patient journeys were exclusively selected if their initiation points were certain. MethodsData underwent rigorous preprocessing, merging, and filtering to create a single event log file suitable for process mining. Patients were categorized by age and medication use, and differences in patient journeys were analyzed. Process mining techniques generated visualizations illustrating the connections between care forms and the impact of changes in one form on others. ResultsThe study included 3,177,203 individuals aged 65 years and older, with 44% experiencing 1 or more patient journeys totaling 2,469,663 journeys in 2017-2019. Most care journeys for older adults were simple and short. The top 10 most frequent journeys had 4 or fewer care forms, with 95% of journeys for the 65+ population and 90% for the 85+ population having 4 or fewer care transitions. Long-term care forms, such as home care, personal care, and long-term care, accounted for the majority of time spent in the system. Conclusions and ImplicationsThis pioneering study used process mining to show that most older adults tend to have a straightforward health care need, often involving the emergency department and hospitalizations. However, a smaller group among the population requires more complex and prolonged care, especially in the 85+ population. Reducing the number of transitions for this population, although impacting fewer people, might result in a larger effect on the overall system.

Predicting the impact of climate change on the potential geographical distribution and growth index of mirid predator, Nesidiocoris tenuis (reuter) (Heteroptera: Miridae) using CLIMEX

Predicting the impact of climate change on the potential geographical distribution and growth index of mirid predator, Nesidiocoris tenuis (reuter) (Heteroptera: Miridae) using CLIMEX