Socioeconomic Vulnerability Research Articles

Heated Environment, Armed People: Between “Climate Change Conflict” and “Fragility Conflict” in the Sahel

The Sahel is a classic example of a region inundated by climate change and conflicts. The region is an ecological hotspot that is on the brink of collapse, as countries in the area are trapped in a vicious cycle of conflict, resource scarcity, and environmental threats, which increase the chances of political instability and civil unrest. Noting that there is a divergent scholarly viewpoint on the relationship between climate change and conflict, this study evaluates the climate change-conflict thesis vis-à-vis the fragility-conflict thesis. It argues that armed conflicts in the Sahel are not exclusively attributable to climate change; rather, other conventional drivers exacerbate the impact of climate change on conflicts. These conventional drivers, framed as fragility indices, play a more significant role in conflict escalation in the Sahel. To this end, this study provides a holistic perspective on conflict dynamics and underscores the intricate interplay between fragility and conflict proliferation. This study adopts a qualitative approach and analyzes secondary data, particularly journal articles, reports, briefs, and developmental indices. The findings show that conditions symptomatic of a fragile state increase the incidence and proliferation of armed conflict in the region. Thus, conflict in the Sahel is a product of amplified pre-existing socioeconomic vulnerabilities and governance challenges.

Socio-Economic Profile and Vulnerabilities Assessment in Small-Scale Fisheries of Lower Gangetic Flood Plain Wetland: An Initiative Towards Achieving Wetland Ecosystem Sustainability and Community Well-Being

ICAR-CIFRI has been continuously working to develop wetland fisheries in a transdisciplinary knowledge-to-action mode to upscale the livelihood of vulnerable small-scale fishermen communities. The integrated development approach was initiated in different lower Gangetic floodplain wetlands of North 24 Parganas, West Bengal, India, to increase the fish production and socio-economic development of small-scale fishermen communities of the wetlands. Duma is one of the most extensive horseshoe-shaped wetlands in Asia. To augment the fish production from this wetland, the pen culture system was adopted by the fishers under the supervision of ICAR-CIFRI in 2021. Within a year, they received 15 tons of commercial fish, valued at around 30 lakhs apart from the small indigenous fish. It has recently been advised that auto-stocked, high-value minor carp in the wetland be adopted to improve income and conserve small indigenous species. In this article, SDG 14 (Life below water) addresses sustainable ecosystem management and livelihood enhancement for the wellbeing of the local people (SDG 3). Nutritional security of the local people is maintained through the small indigenous fish species which is crucial for addressing ‘No hunger’ as per SDG-2. The research also proves that women can play a crucial role in small-scale fisheries and they can economically stand alone, which is the main aim of SDG-5 (gender equality). However, significant issues such as lack of jurisdictional coordination, ecological changes, inequitable distribution of benefits, and income reduction persist in wetland management. The need for urgent reformation of policy and resource management systems is crucial to boost the economic efficiency of the SSF in the wetland. Training for more knowledge on fishing and fish farming, acquiring alternative livelihood and education on financial management should be brought to the fishermen’s communities. These could develop a resilient community that is more equipped to respond to future crises.

Assessment of socio-economic strategies for managing regional flood risk in an urban coastal catchment

With the cascading flooding events over the past decades, several structural and non-structural measures have been effectively implemented for improved flood management. However, the uneven impacts of the flooding events have highlighted that socio-economic inequality amongst the community needs to be addressed along with hazards to devise long term and sustainable flood management strategies. This study aims to evaluate the impact of socio-economic adaptive scenarios over an urban coastal catchment for reduction in flood risk. Flood risk is estimated utilizing socio-economic aspects (vulnerability) and flood inundation (hazard), for the highly flood-prone coastal city of Mumbai, India. A multivariate approach is used for assessing socio-economic vulnerability, starting with Principal Component Analysis followed by Data Envelopment Analysis, for various socio-economic scenarios, i.e., by reducing percentage of certain feasible socio-economic sensitivity indicators, to identify the key indicators, which contribute to significant change in vulnerability. The flood hazard is assessed through a comprehensive hydrodynamic flood modelling approach to quantify the flood inundation depth and extent. The flood risk is, thereafter, evaluated by combining socio-economic vulnerability and flood hazard using bivariate risk mapping approach. The results indicate that, with the decrease in alteration percentage of certain feasible socio-economic sensitivity indicators, the overall vulnerability and flood risk may be reduced. The areas under very high and high vulnerability classes reduce gradually for all scenarios as the percentage reduction for various indicators is varied from 5 % to 15 %, total illiteracy being the most significant indicator. This study marks the first effort to discern socio-economic vulnerability indicators that have the potential to significantly diminish flood risk, thereby constituting a viable long-term flood risk mitigation strategy. This novel framework is generic and applicable to any flood prone catchments, to devise appropriate long-term flood management measures.

Assessment of Socioeconomic Vulnerability in Selected Villages of Gosaba Block, Sundarban, India Using an Artificial Neural Network

The Indian Sundarban represent an endangered ecosystem with a distinct biogeographical composition. It is susceptible to natural disasters like storms, floods, and cyclones, hence jeopardizing its socioeconomic systems due to environmental stresses. This study aimed to evaluate the present socioeconomic vulnerability, identify key factors that exacerbate this vulnerability, and validate these factors using an Artificial Neural Network (ANN) prediction model. Researchers also wanted to validate this evaluation with ANN to promote substantive discussions between researchers, local authorities, and stakeholders. Comprehensive reviews and successful adaption plans will improve. The study conducted in selected villages with 160 households in the Gosaba Block, located on the periphery of the Sundarban. The present study employed an integrated vulnerability approach, calculating the exposure, adaptive capacity, and sensitivity index by weighting the initial eigenvalues of each indicator with a variance percentage through principal components analysis (PCA). Based on this criterion, 156 households (97.5%) exhibited an extremely high vulnerability score, while 4 households (2.5%) displayed a moderate vulnerability grade. The villages of Pakhiralay and Lahiripur exhibit significant vulnerability, with a markedly deficient adaptive capacity. The villages of Mathurakhand, Kumirmari, and Satjelia exhibit vulnerability alongside moderate adaptation capacity. All are priority villages, however, Villages with moderate adaptive capacity may become less vulnerable with adequate interventions Proximity to market strongly affects MLP neural networks' assessment of environmental, economic, and social variables' effects on exposure, sensitivity, and adaptive capacity. Respondent age, family size, social network, storm surges, supplementary sources of household income Dwelling years, temperature, embankment failure, and income greatly affect model performance. A policy initiative should prioritize the enhancement existing social and financial capital, facilitate access to local government, and promote community-oriented activities. National disaster, social welfare, and resource management strategies need separate action plans. The national government is also encouraged to decentralize governance to enable local governments to achieve their goals.

Understanding and monitoring vulnerability during pregnancy at population-level

Abstract Background Detecting and addressing vulnerability during pregnancy is important to optimize the first thousands days of children’s lives and prevent health inequities. We aimed to gain insight into vulnerability during pregnancy and determine the best data to predict vulnerability. Methods In the Netherlands, two studies were done using nationwide routinely collected data and self-reported Public Health Monitor-data. The first study utilized all data to identify classes of vulnerability among 4172 pregnant women through Latent Class Analysis. The second study predicted multidimensional vulnerability at population-level using solely routinely collected data first, and step-by-step incorporating self-reported data. Random Forest (RF) analysis was employed, and model performance was assessed using Area Under the Curve (AUC) and F1-measure. Results Five vulnerability-classes were found: ‘healthy and socioeconomically stable’, ‘high care utilization’, ‘socioeconomic vulnerability’, ‘psychosocial vulnerability’, and ‘multidimensional vulnerability’. Women in the ‘multidimensional vulnerability’-class shared multiple risk factors across domains and lacked protective factors. They more often had adverse outcomes such as premature birth. In the next study, the initial RF-model achieved an AUC of 0.98 in distinguishing multidimensional vulnerability, with an F1-measure of 0.70. Adding self-reported data improved model performance. Strong predictors were self-reported health, socioeconomic characteristics and healthcare utilization. Conclusions Several vulnerability classes can be distinguished among pregnant women. The co-existence of risk factors and lack of protective factors leads to more adverse outcomes. Effective public health strategies should include both medical and social care and support. Next, it seems possible to predict multidimensional vulnerability using data that is readily available, providing a foundation for longitudinal monitoring and policy formulation. Key messages • Considering the combination of both social risk and protective factors related to vulnerability during pregnancy is necessary. • Routinely collected data could provide insight in the prevalence, geographical distribution and trends in multidimensional vulnerability during pregnancy at population-level.

An intersectional approach on menstrual inequity as lived by women in circumstances of socioeconomic vulnerability in an urban and rural setting in Spain: a qualitative study

Since menstrual health and menstrual inequity are determined by social power structures, this study proposes to analyse, from an intersectional perspective, the experiences of menstrual inequity of women and people who menstruate (PWM) (≥18 years) under circumstances of socioeconomic vulnerability in an urban and rural setting in Catalonia (Spain), focusing on menstrual poverty, menstrual management and access to health care for menstrual health. An exploratory and interpretative qualitative study was conducted. Venue-based convenience sampling was carried out, recruiting women from a non-governmental organisation and a primary health care centre. Eighteen individual semi-structured interviews were conducted between October 2022 and February 2023. Data were analysed through reflexive thematic analysis. Analysis revealed that menstrual care was generally a distant preoccupation that revolved around circumstances of socioeconomic vulnerability, housing, and productive/reproductive work. Menstrual poverty, menstrual management and menstrual self-care challenges, barriers to accessing health care for menstrual health, and menstrual taboo, stigma and discrimination were commonplace and deepened by socioeconomic vulnerability. In this way, women’s menstrual experiences were rooted in intersecting axes of inequity, based on gender, race and class. Intersectional and critical participatory research, policy and practice are imperative to develop counter mechanisms that confront systems of privilege-oppression to modulate menstrual experience, health and equity.

System-wide health needs segmentation: innovating integrated care for complex needs households

Abstract Background Health needs segmentation is increasingly used in healthcare delivery and health policy planning to cater for diverse population groups and develop effective and equitable health policies. But existing models often lack a systemic approach, focusing instead on single conditions or settings. This leads to fragmentation, gaps and inefficiencies in service provision and inequities in health outcomes, particularly when addressing complexity, and specifically for children, as adversity clusters in families. Aims To develop a household health needs segmentation model to identify those households with children with high levels of complex cross-sectoral needs, to plan for integrated care services. Methods Data linkage of primary, secondary, mental, community and social care services, mortality records, residential information, and small-area multiple deprivation measures was used to design a rule-based model to identifying households with children with the most complex needs in the UK region of Cheshire and Merseyside (C&M), with large variation in demography, (human) geography, and deprivation. Results Of 2,645,329 individuals in C&M (97% of the registered population in 2021), 1,022,840 lived in 266,939 households with children aged 0-16: 21,527 households had complex needs. This 8% of families accounted for an estimated 34% of health and social care costs for families, £362 million in total, 42% of which spent on children in care of local authorities. Implications The model identified a specific group of families with complex service use patterns, high mental and physical comorbidity and socioeconomic vulnerabilities. These exhibit potential for improved outcomes through better integration of services and targeting of community building and family support resources. Conclusions Our model represents a significant innovation in health needs segmentation. By using whole system linked data, it provides a pragmatic way of profiling complexity for proactive care. Key messages • Complex health and social problems in children cluster in families with adults also having complex needs, so we need to transform fragmented services to support the whole family to improve outcomes. • Household level segmentation using cross-sectoral, whole system data is an innovation to identify households with complex needs with respect to their locality to improve integration of support.

Delineating the drought vulnerability zones in Bangladesh

The research aims to explore the vulnerability of Bangladesh to drought by considering a comprehensive set of twenty-four factors, classified into four major categories: meteorological, hydrological, agricultural, and socioeconomic vulnerability. To achieve this, the study utilized a knowledge-based multi-criteria method known as the Analytic Hierarchy Process (AHP) to delineate drought vulnerability zones across the country. Weight estimation was accomplished by creating pairwise comparison matrices for factors and different types of droughts, drawing on relevant literature, field experience, and expert opinions. Additionally, online-based interviews and group discussions were conducted with 30 national and foreign professionals, researchers, and academics specializing in drought-related issues in Bangladesh. Results from overall drought vulnerability map shows that the eastern hills region displays a notably high vulnerability rate of 56.85% and an extreme low vulnerability rate of 0.03%. The north central region shows substantial vulnerability at high levels (35.85%), while the north east exhibits a significant proportion (41.68%) classified as low vulnerability. The north west region stands out with a vulnerability rate of 40.39%, emphasizing its importance for drought management strategies. The River and Estuary region displays a modest vulnerability percentage (38.44%), suggesting a balanced susceptibility distribution. The south central and south east regions show significant vulnerabilities (18.99% and 39.60%, respectively), while the south west region exhibits notable vulnerability of 41.06%. The resulting model achieved an acceptable level of performance, as indicated by an area under the curve value of 0.819. Policymakers and administrators equipped with a comprehensive vulnerability map can utilize it to develop and implement effective drought mitigation strategies, thereby minimizing the losses associated with drought.

Importance of Eco-Entrepreneurship as a Tool for Climate Action and LowCarbon Transition in Developing Countries: A Case Study of Nigeria

Climate change poses socio-economic, legal and environmental vulnerabilities such as land degradation, biodiversity loss, loss of property and livelihood, increase poverty rate and a threat to public health. These impacts are said to only intensify with projected increase in population and global economic growth. Hence, global consensus advocate for decarbonisation and low carbon transition in all economic sectors as an effective mitigation strategy for climate change. In an attempt to lower carbon emissions, leading cooperation’s and organizations have focused on mitigation projects that regulate activities of cooperate actors and big CO2 emitters such as the oil and gas conglomerates. However, the United Nation Sustainability Development Goals (SDGs) promotes a transformative bottom-up approach to address climate change via localism and citizen participation to educate and train eco-entrepreneurs or ecopreneurs who participate and engage in strategic entrepreneurship projects designed to actively decarbonize economies. These ecopreneurs generate home-grown sustainabilityfocused small and medium scale eco-enterprises (SMEEs), also called energy citizens, ecological citizens, energy communities and co-operatives that can develop sustainable business model innovations, nature-based services and solutions, sustainable business management strategies, technologies and green jobs needed to drive the low carbon transition in key CO2 -emitting economic sectors such as the energy, agriculture, transportation, waste management, food, tourism, building and architecture and fashion industries. This article examines the characteristics, nature and benefits of eco-entrepreneurship as a tool for advancing climate action and low carbon energy transition. Using Nigeria as a case study, a profile of the barriers slowing the growth of eco-entrepreneurship is identified within the PESTEL framework. Furthermore, drawing examples from the U.K. governance landscape and portfolio, recommendations on a transformative yet contextual strategy captured in the five transformative features (diversity, connectivity, polycentricity, redundancy and directionality) are made to interrogate and overcome entrepreneurial ecosystem barriers towards successfully supporting the rapid growth of eco-entrepreneurship.

The prevalence of overweight among 4-year-olds during and after the COVID-19 pandemic was associated with socioeconomic burden.

To assess the prevalence of overweight among Swedish 4 year olds in 2018, 2020 and 2022, taking socioeconomic variables into account. Aggregated regional data on children's body mass index were collected. The socioeconomic Care Need Index (CNI), foreign background, low education, being a single parent, low income and childhood poverty, were assessed. The differences in overweight, including obesity, were tested for Sweden and for regions. Data were available for 303 843 children, representing 87% of children born in 2014, 2016 and 2018. Overweight or obesity were found in 11 177 (11.4%) of children in 2022, decreasing from 2020 (13.3%, p < 0.001) but at the same level as in 2018. Regional low CNI, low level of foreign background, education and income as well as being a single parent were associated with a higher prevalence of overweight or obesity in all cohorts (p < 0.001). In regions with high levels of childhood poverty, overweight or obesity were more prevalent during (p = 0.009) and after the pandemic (p < 0.001). Three national cohorts demonstrate that the increase in overweight during the COVID-19 pandemic has returned to pre-pandemic levels, but the inequalities in health associated with socioeconomic vulnerability of the regions remained.

Environmental and Humanitarian Law Violations in Bangladesh's Coastal Areas: A Survey Analysis

This study investigates the intersection of environmental and humanitarian law violations in the coastal areas of Bangladesh, focusing on the implications of climate change-induced disasters on vulnerable communities. A quantitative survey was conducted, with 150 respondents representing coastal regions, to gather data on the prevalence of environmental degradation, climate-induced displacement, and human rights violations. Findings reveal a significant correlation between environmental hazards, such as cyclones and sea-level rise, and the displacement of coastal populations, exacerbating socio-economic vulnerabilities and human rights abuses. The study employs a quantitative methods design, analyzing survey data of legal frameworks, policy documents, and scholarly literature. The data was analyzed through Smart PLS 4 for Structural Equational Model (SEM). The purpose of this research is to elucidate the complexities surrounding legal enforcement, policy implementation, and grassroots initiatives aimed at addressing environmental and humanitarian challenges in coastal areas. By providing empirical evidence and insights into the lived experiences of affected communities, this study aims to inform evidence-based policy interventions, legal reforms, and humanitarian strategies to enhance resilience and protect the rights of coastal populations facing the impacts of climate change and environmental degradation.

Assessment of socioeconomic and health vulnerability among urban slum dwellers in Bangladesh: a cross-sectional study

BackgroundBangladesh is rapidly urbanizing and approximately half of its urban population resides in deprived slums with limited access to basic needs. However, there is a dearth of information on vulnerability levels among slum dwellers. We aimed to assess the level of vulnerability within and between slums via various socioeconomic and health indicators.MethodsA cross-sectional survey of 810 randomly selected households was conducted in two purposively selected slums, Korail and Shyampur, in Dhaka from November to December 2021. Data was collected on various indicators, including demographics, education, employment, access to utility, and healthcare services. Principal component factor analysis was employed to identify the key indicators to construct the socioeconomic and health vulnerability index for the urban slums of Bangladesh (SEHVI-BD). Kaiser-Meyer-Olkin, Bartlett’s test, and Cronbach’s alpha coefficient test were used to assess indicators’ suitability. The selected indicators were used to generate an index on a scale of 100, with a higher index value indicating a higher level of vulnerability. The estimated scores were used to categorize the vulnerability status into three levels: mild, moderate, and severe vulnerability. The Mann-Whitney-U test and Kruskal-Wallis test were applied between the generated index and other socioeconomic variables to validate the relationship.ResultsA total of 27 socioeconomic and health indicators were identified that explained 60% of the variance. The indicators were then grouped into six domains on the basis of their relevance. The prevalence of severe vulnerability in the Korail slum was approximately 9% and moderate vulnerability was 30% whereas these values were approximately 58% and 37%, respectively, in the Shyampur slum. The difference in the vulnerability level between the two slums was also evident across the domains. Households in the poorest wealth quintile, with lower education levels of household heads, and having irregular income experienced higher levels of vulnerability.ConclusionsThe SEHVI-BD offers a critical tool for policymakers to identify and address vulnerabilities, facilitating more targeted public health interventions in urban Bangladesh and similar low-income settings. This study further emphasizes the importance of integrating comprehensive vulnerability assessments into public health policies to reduce inequalities and improve well-being, especially for the urban marginalized slum population.

Modeling climate-related global risk maps of rice bacterial blight caused by Xanthomonas oryzae (Ishiyama 1922) using geographical information system (GIS).

Rice is a critical staple crop that feeds more than half of the world's population. Still, its production confronts various biotic risks, notably the severe bacterial blight disease produced by Xanthomonas oryzae. Understanding the possible effects of climate change on the geographic distribution of this virus is critical to ensuring food security. This work used ecological niche modeling and the Maxent algorithm to create future risk maps for the range of X. oryzae under several climate change scenarios between 2050 and 2070. The model was trained using 93 occurrence records of X. oryzae and five critical bioclimatic variables. It has an excellent predictive performance, with an AUC of 0.889. The results show that X. oryzae's potential geographic range and habitat suitability are expected to increase significantly under low (RCP2.6) and high (RCP8.5) emission scenarios. Key climatic drivers allowing this development include increased yearly precipitation, precipitation during the wettest quarter, and the wettest quarter's mean temperature. These findings are consistent with broader research revealing that climate change is allowing many plant diseases and other dangerous microbes to spread across the globe. Integrating these spatial predictions with data on host susceptibility, agricultural practices, and socioeconomic vulnerabilities can help to improve targeted surveillance, preventative, and management methods for reducing the growing threat of bacterial blight to rice production. Proactive, multidisciplinary efforts to manage the changing disease dynamics caused by climate change will be critical to assuring global food security in the future decades.

Blinders of extreme heat adaptation: uneven urban development and the reproduction of vulnerabilities

ABSTRACT Despite its deadly nature, extreme heat has received fragmented and scattered responses in cities, often overlooking the crucial social and equity components. Dominant adaptation approaches have paid little attention to chronic socio-economic vulnerabilities to heat stress, resulting in a lack of strategic planning to address them. Building upon critical urban studies and adaptation scholarship, this article examines how the dynamics of urban climate adaptation in the Global North have sidestepped the root causes of heat vulnerability and their (re)production in past, present and future practices of uneven urban development and planning under austerity. We investigate this empirically in attending to the framing of adaptation, the instruments used and the biases they introduce in Montreal (Canada), as well the perception from planners and community groups regarding their agency in responding to extreme heat. We contribute to the literature in analysing how the urban governance of adaptation in urban planning tends to silence the social production of vulnerabilities by three intersecting processes: the biases of instruments used, the unacknowledged legacies of uneven urban development, and the lacking recognition and support for community organisations caring practices.

Integrating social, climate and environmental changes to confront accelerating global aging

IntroductionThe global increase in the aging population presents critical challenges for healthcare systems, social security, and economic stability worldwide. Although the studies of the global rate of aging have increased more than four times in the past two decades, few studies have integrated the potential combined effects of socio-economic, climatic, and environmental factors.MethodsWe calculated the geographic heterogeneity of aging population growth rates from 218 countries between 1960 and 2022. Public databases were then integrated to assess the impacts of seven global stressors: socio-economic vulnerability, temperature, drought, seasonality, climate extremes, air pollution, and greening vulnerability on growth rates of aging population (a totally 156 countries). Linear regression models were primarily used to test the statistically significant effects of these stressors on the rate of aging, and multiple model inference was then used to test whether the number of stressors exceeding specific thresholds (e.g., > 25, 50, and 75%) was consistently significant in the best models. The importance of stressors and the number of stressors exceeding thresholds was verified using random forest models for countries experiencing different population aging rates.ResultsOur analysis identified significant heterogeneity in growth rates of aging population globally, with many African countries exhibiting significantly lower aging rates compared with Europe. High socio-economic vulnerability, increased climate risks (such as high temperature and intensive extreme climate), and decreased environmental quality were found to significantly increase growth rates of the aging population (P < 0.05). The positive combined impacts of these stressors were diminished at medium–high levels of stressors (i.e., relative to their maximum levels observed in nature). The number of global stressors exceeding the 25% threshold emerged as an important predictor of global aging rates. Demographic changes in regions with relatively rapid aging (e.g., Africa and Asia) are more sensitive to climate change (e.g., extreme climate and drought) and the number of global stressors, and regions with low to medium rates of aging (e.g., Europe and the Americas) are more sensitive to socio-economic vulnerability and environmental stability (e.g., drought, green fragility and air pollution).ConclusionsOur findings underscore that policy tools or methods must be developed that consider the holistic dimension of the global factor. Further investigations are essential to understand the complex interactions between multiple stressors and their combined effects on global aging.

Socio-economic vulnerability assessment of culturally unique ethnic communities using RIDIT scoring: a case of Rann of Kutch, India

Socio-economic vulnerability assessment of culturally unique ethnic communities using RIDIT scoring: a case of Rann of Kutch, India

HeatReady Neighborhoods: A Planning Rubric for Extreme Heat

Problem, research strategy, and findings Rising temperatures and prolonged heat waves present significant challenges for all communities and are further exacerbated by socioeconomic and spatial vulnerabilities. Extreme heat impacts are amplified in areas with historic underinvestment in infrastructure, discriminatory redlining practices, and limited access to cooling amenities. To ethically mitigate and adapt to these impacts, holistically addressing urban heat impacts and coping strategies at the neighborhood level is crucial. Here we present the development of a HeatReady Neighborhoods planning rubric, co-created with community members and academic partners. The rubric evaluated overall HeatReady performance levels based on community-specific values and served as a modular template for assessing heat readiness using the Phoenix (AZ) metropolitan region as a case study. Takeaway for Practice By prioritizing hyperlocal, neighborhood-scale needs, the planning rubric can enable communities to optimize their social, physical, and natural assets for improved resilience to extreme heat and other slow-moving natural hazards. This adaptable model can guide planners, city officials, and community leaders in co-creating strategies with neighborhoods to effectively identify, mitigate, and build adaptation to the adverse effects of extreme heat, filling a gap in mainstream, agency-led heat action planning.

Performance of the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) Model in the Northeast Region of Brazil

Study is presented on the potential for using the tools contained in the Google Earth Engine (GEE) geospatial data processing and analysis platform in climatological studies in the Northeast Region of Brazil (NEB), in particular the validation of estimates of total annual rainfall obtained by the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) model in seven homogeneous regions of the NEB. This data is made up of various sources of meteorological information, including information from satellites, numerical models and observations at weather stations in operational and research centers across the globe. The performance of the CHIRPS model was assessed using climatological data obtained from the National Meteorological Institute's (INMET) meteorological database, metrics and statistical tests. The results showed that the CHIRPS model has potential for use in six of the seven regions studied, with low errors and strong statistical correlation, and limitations in one of these regions. The conclusion is that this technological tool, which has a low operating cost and is free of charge, can be used to assist in climatological studies, planning and the development of strategies for mitigation, adaptation and coexistence with the dry periods observed in the sub-regions of the NEB, especially in regions that are in a situation of socio-economic vulnerability, as is the case in the semi-arid region of the NEB.

Community-Level Social Vulnerability and Hip and Knee Joint Replacement Surgery Receipt Among Medicare Enrollees With Arthritis.

(1) Explore associations between county minority health social vulnerability index (MH-SVI) and total joint replacement (TJR), and (2) assess associations by individual-level race/ethnicity. An expanded understanding of relevant social determinants of health is essential to inform policies and practices that promote equitable access to hip and knee TJR. Retrospective cohort study of Medicare enrollees. Centers for Medicare and Medicaid Services claims data were linked with MH-SVI. Multivariable logistic regression models were used to evaluate the odds of TJR according to the MH-SVI quartile in which enrollees resided. A total of 10,471,413 traditional Medicare enrollees in 2018 aged 67 years or older with arthritis. The main outcome was enrollee primary TJR during hospitalization. The main exposure was the MH-SVI (composite and 6 themes) for the county of enrollee residence. Results were stratified by enrollee race/ethnicity. Asian American, Native Hawaiian, or Pacific Islander (AANHPI), Black or African American (Black), and Hispanic enrollees comparatively had 26%-41% lower odds of receiving TJR than White enrollees. Residing in counties within the highest quartile of composite and socioeconomic status vulnerability measures were associated with lower TJR overall and by race/ethnicity. Residing in counties with increased medical vulnerability for Black and White enrollees, housing type and transportation vulnerability for AANHPI and Hispanic enrollees, minority status and language theme for AANHPI enrollees, and household composition vulnerability for White enrollees were also associated with lower TJR. Higher levels of social vulnerability were associated with lower TJR. However, the association varied by individual race/ethnicity. Implementing multisectoral strategies is crucial for ensuring equitable access to care.

Non-optimum temperatures led to labour productivity burden by causing premature deaths: A multi-country study

BackgroundNon-optimum temperatures are associated with a considerable mortality burden. However, there is a lack of evaluation of labour productivity losses related to premature deaths due to non-optimum temperatures. This study aimed to quantify the labour productivity burden associated with premature deaths related to non-optimum temperatures and explore the potential socio-economic vulnerabilities. MethodsDaily all-cause mortality data were collected from 1,066 locations in 7 countries (Australia, Brazil, Canada, Chile, New Zealand, South Korea, and Thailand). Productivity-Adjusted Life-Year (PALY) loss due to each premature death was calculated to measure the labour productivity loss, by multiplying the years of working life lost by the proportion of the equivalent full-time (EFT) workers. A two-stage times series design and the generalized linear regression model with a quasi-Poisson family were applied to assess the association between non-optimum temperatures and the PALY loss due to premature deaths. ResultsWe observed a U-shaped relationship between temperature and PALY lost due to premature mortality. We estimated that 2.51% (95% eCI: 2.05%, 2.92%) of PALY losses could be attributed to non-optimal temperatures, with cold-related deaths contributing 1.26% (95% eCI: 0.94%, 1.54%) and heat-related deaths contributing 1.25% (95% eCI: 0.96%, 1.51%). Cold temperature contributed to the most PALYs lost in those aged 45–54 and 55–64, while heat-related losses predominated among the 15–44 age group. We also observed that the fractions of PALY lost attributed to extreme heat were positively associated with the relative deprivation index, while negatively associated with GDP per capita. ConclusionThis multi-country study highlights that non-optimum temperatures led to a considerable labour productivity loss and socioeconomically disadvantaged communities experience greater losses.