Displaying publications 61 - 80 of 274 in total

Abstract:
Sort:
  1. The impact of climate variables on marine fish production: an empirical evidence from Bangladesh based on autoregressive distributed lag (ARDL) approach
    Begum M, Masud MM, Alam L, Mokhtar MB, Amir AA
    Environ Sci Pollut Res Int, 2022 Dec;29(58):87923-87937.
    PMID: 35819668 DOI: 10.1007/s11356-022-21845-z
    Several studies have highlighted the significant impact of climate change on agriculture. However, there have been little empirical enquiries into the impact of climate change on marine fish production, particularly in Bangladesh. Hence, this study aims to investigate the impact of climate change on marine fish production in Bangladesh using data from 1961 to 2019. Data were obtained from the Food and Agriculture Organization, Bangladesh Meteorological Department, the World Development Indicators, and the National Oceanic and Atmospheric Administration. The autoregressive distributed lag (ARDL) model was used to describe the dynamic link between CO2 emissions, average temperature, Sea Surface Temperature (SST), rainfall, sunshine, wind and marine fish production. The ARDL approach to cointegration revealed that SST (β = 0.258), rainfall (β =0.297), and sunshine (β =0.663) significantly influence marine fish production at 1% and 10% levels in the short run and at 1% level in the long run. The results also found that average temperature has a significant negative impact on fish production in both short and long runs. On the other hand, CO2 emissions have a negative impact on marine fish production in the short run. Specifically, for every 1% rise in CO2 emissions, marine fish production will decline by 0.11%. The findings of this study suggest that policymakers formulate better policy frameworks for climate change adaptation and sustainable management of marine fisheries at the national level. Research and development in Bangladesh's fisheries sector should also focus on marine fish species that can resist high sea surface temperatures, CO2 emissions, and average temperatures.
    Matched MeSH terms: Climate Change
  2. Fulltext Measuring Pro-Environmental Behavior Triggered by Environmental Values
    Ahmat Zainuri N, Abd-Rahman N, Halim L, Chan MY, Mohd Bazari NN
    Int J Environ Res Public Health, 2022 Nov 30;19(23).
    PMID: 36498088 DOI: 10.3390/ijerph192316013
    Pro-environmental behavior in addressing climate change is influenced by multi-dimensional factors-knowledge, values, intention and sociodemographic background. Correlational studies between environmental values and environmental behaviors have not been able to determine values or behaviors that need to be given priority in future interventions. Therefore, this study firstly determined the environmental values and pro-environmental behavior that are easy or difficult to embrace by 152 respondents with low socioeconomic background. Secondly, we identified the extent pro-environmental behavior is triggered by environmental values. This survey study employs the Rasch analysis model. The respondents had difficulty in associating themselves with biospheric values however readily demonstrated consideration toward altruistic values, especially related to concerns for future generations. In terms of environmental conservation behavior, the respondents were not willing to relinquish comfort easily, such as giving up self-driving and taking public transportation or reducing usage of electricity. In addition, adults of low socioeconomic background find it difficult to endorse statements such as getting involved in campaigns related to environmental conservation. Thus, younger family members must be educated about conservation behaviors such as environmental campaigns commonly offered at schools, and these youngsters can be encouraged to extend their role by educating their parents.
    Matched MeSH terms: Climate Change*
  3. The 2022 report of the Lancet Countdown on health and climate change: health at the mercy of fossil fuels
    Romanello M, Di Napoli C, Drummond P, Green C, Kennard H, Lampard P, et al.
    Lancet, 2022 Nov 05;400(10363):1619-1654.
    PMID: 36306815 DOI: 10.1016/S0140-6736(22)01540-9
    Matched MeSH terms: Climate Change*
  4. Protect global values of the Southern Ocean ecosystem
    Brooks CM, Ainley DG, Jacquet J, Chown SL, Pertierra LR, Francis E, et al.
    Science, 2022 Nov 04;378(6619):477-479.
    PMID: 36264826 DOI: 10.1126/science.add9480
    Climate change and fishing present dual threats.
    Matched MeSH terms: Climate Change*
  5. Fulltext Tiger sharks support the characterization of the world's largest seagrass ecosystem
    Gallagher AJ, Brownscombe JW, Alsudairy NA, Casagrande AB, Fu C, Harding L, et al.
    Nat Commun, 2022 Nov 01;13(1):6328.
    PMID: 36319621 DOI: 10.1038/s41467-022-33926-1
    Seagrass conservation is critical for mitigating climate change due to the large stocks of carbon they sequester in the seafloor. However, effective conservation and its potential to provide nature-based solutions to climate change is hindered by major uncertainties regarding seagrass extent and distribution. Here, we describe the characterization of the world's largest seagrass ecosystem, located in The Bahamas. We integrate existing spatial estimates with an updated empirical remote sensing product and perform extensive ground-truthing of seafloor with 2,542 diver surveys across remote sensing tiles. We also leverage seafloor assessments and movement data obtained from instrument-equipped tiger sharks, which have strong fidelity to seagrass ecosystems, to augment and further validate predictions. We report a consensus area of at least 66,000 km2 and up to 92,000 km2 of seagrass habitat across The Bahamas Banks. Sediment core analysis of stored organic carbon further confirmed the global relevance of the blue carbon stock in this ecosystem. Data from tiger sharks proved important in supporting mapping and ground-truthing remote sensing estimates. This work provides evidence of major knowledge gaps in the ocean ecosystem, the benefits in partnering with marine animals to address these gaps, and underscores support for rapid protection of oceanic carbon sinks.
    Matched MeSH terms: Climate Change
  6. The plight and promise of mental health providers in the face of a warming planet: perspectives and experiences from the Philippines
    Aruta JJBR, Salcedo SS, Guilaran J, Guinto RR
    Int Rev Psychiatry, 2022 08;34(5):530-533.
    PMID: 36165758 DOI: 10.1080/09540261.2022.2123701
    A growing body of research shows the inimical impact of climate change on people's mental health. However, attention to mental health providers at the frontlines is rather sparse, especially in climate-vulnerable countries. This commentary aims to present the perspectives and experiences of mental health providers within the context of climate change in the Philippines. Specifically, this paper explicates the challenges faced by mental health providers in trying to address the increasing climate-related distress experienced by many Filipinos and the recent progress in promoting climate change and mental health nexus in the country. The recommendations offered in this commentary will hopefully provide the basis for a more comprehensive mental health framework that incorporates climate change and supports mental health providers in their pursuit to preserve Filipino mental health on a warming planet.
    Matched MeSH terms: Climate Change
  7. The role of mental health professionals in the climate crisis: an urgent call to action
    Li C, Lawrance EL, Morgan G, Brown R, Greaves N, Krzanowski J, et al.
    Int Rev Psychiatry, 2022 08;34(5):563-570.
    PMID: 36165755 DOI: 10.1080/09540261.2022.2097005
    The climate and ecological crisis will constitute the defining public health challenge of the twenty-first century, posing an unprecedented global threat to all determinants of health, and to healthcare delivery systems. We believe that mental health professionals have a crucial role to play in responding to this crisis. Whilst responding to the mental health consequences of the climate crisis will remain a key role for us as mental health professionals, we argue that our remit goes beyond this, and should include advancing public understanding of the climate crisis, highlighting its impact on physical and mental wellbeing, and advocating for systemic changes to limit its impending harms. This paper is an urgent call to action for all mental health professionals to take up a role in the context of the climate and ecological crisis. This paper will describe the relationship between mental health and climate change, and frame it within wider systemic and conceptual frameworks. It will demonstrate that as mental health professionals we are well placed to act as leaders of change-arguing that we have a duty to do so-and suggest actions that can be implemented depending on interests, skill sets and opportunities.
    Matched MeSH terms: Climate Change*
  8. The role of economic complexity in the environmental Kuznets curve of MINT economies: evidence from method of moments quantile regression
    Adebayo TS, Rjoub H, Akadiri SS, Oladipupo SD, Sharif A, Adeshola I
    Environ Sci Pollut Res Int, 2022 Apr;29(16):24248-24260.
    PMID: 34822076 DOI: 10.1007/s11356-021-17524-0
    In the face of mounting climate change challenges, reducing emissions has emerged as a key driver of environmental sustainability and sustainable growth. Despite the fact that research has been conducted on the environmental Kuznets curve (EKC), few researchers have analyzed this in the light of economic complexity. Thus, the current research assesses the effect of economic complexity on CO2 emissions in the MINT nations while taking into account the role of financial development, economic growth, and energy consumption for the period between 1990 and 2018. Using the novel method of moments quantile regression (MMQR) with fixed effects, an inverted U-shape interrelationship is found between economic growth and CO2 emissions, thus validating the EKC hypothesis. Energy consumption and economic complexity increase CO2 emissions significantly from the 1st to 9th quantiles. Furthermore, there is no significant interconnection between financial development and CO2 emissions across all quantiles (1st to 9th). The outcomes of the causality test reveal a feedback causal connection between economic growth and CO2, while a unidirectional causality is established from economic complexity and energy use to CO2 emissions in the MINT nations. Based on the findings, we believe that governments should stimulate the financial sector to provide domestic credit facilities to industrialists, investors, and other business enterprises on more favorable terms so that innovative technologies for environmental protection can be implemented with other policy recommendations.
    Matched MeSH terms: Climate Change
  9. Fulltext Climate change and COVID-19: shared challenges, divergent perspectives, and proposed collaborative solutions
    Wahaj Z, Alam MM, Al-Amin AQ
    Environ Sci Pollut Res Int, 2022 Mar;29(11):16739-16748.
    PMID: 34989992 DOI: 10.1007/s11356-021-18402-5
    Pandemics leave their mark quickly. This is true for all pandemics, including COVID-19. Its multifarious presence has wreaked havoc on people's physical, economic, and social life since late 2019. Despite the need for social science to save lives, it is also critical to ensure future generations are protected. COVID-19 appeared as the world grappled with the epidemic of climate change. This study suggests policymakers and practitioners address climate change and COVID-19 together. This article offers a narrative review of both pandemics' impacts. Scopus and Web of Science were sought databases. The findings are reported analytically using important works of contemporary social theorists. The analysis focuses on three interconnected themes: technology advancements have harmed vulnerable people; pandemics have macro- and micro-dimensions; and structural disparities. To conclude, we believe that collaborative effort is the key to combating COVID-19 and climate change, while understanding the lessons learnt from the industrialised world. Finally, policymakers can decrease the impact of global catastrophes by addressing many socioeconomic concerns concurrently.
    Matched MeSH terms: Climate Change
  10. Fulltext A photovoice assessment for illuminating the role of inland fisheries to livelihoods and the local challenges experienced through the lens of fishers in a climate-driven lake of Malawi
    Simmance FA, Simmance AB, Kolding J, Schreckenberg K, Tompkins E, Poppy G, et al.
    Ambio, 2022 Mar;51(3):700-715.
    PMID: 34170476 DOI: 10.1007/s13280-021-01583-1
    Small-scale inland capture fisheries provide an important source of nutritious food, employment and income to millions of people in developing countries, particularly in rural environments where limited alternatives exist. However, the sector is one of most under-valued fisheries sectors and is increasingly experiencing environmental change. This study adopts a Sustainable Livelihoods Approach and investigates how important a fluctuating inland fishery is to livelihoods, and how local perceptions on challenges corresponds to global evidence. Through an innovative participatory method; photovoice, the lived experiences and perceptions of fishers are depicted. The findings illuminate the valuable role of the sector to food and nutrition security and the complex nexus with vulnerability to climate change. The study responds to the call for more local level assessments of the impacts of climate change on inland fisheries in data-limited environments, and the value of the sector in underpinning the Sustainable Development Goals.
    Matched MeSH terms: Climate Change
  11. Assessing the effect of climate change and financial development on agricultural production in ASEAN-4: the role of renewable energy, institutional quality, and human capital as moderators
    Chandio AA, Shah MI, Sethi N, Mushtaq Z
    Environ Sci Pollut Res Int, 2022 Feb;29(9):13211-13225.
    PMID: 34585355 DOI: 10.1007/s11356-021-16670-9
    This paper examines the effect of climate change and financial development on agricultural production in ASEAN-4, namely Indonesia, Malaysia, the Philippines, and Thailand from 1990 to 2016. Further, we explore the role of renewable energy, institutional quality, and human capital on agricultural production. Since the shocks in one country affect another country, we use second-generation modeling techniques to find out the relationship among the variables. The Westerlund (2007) cointegration tests confirm long-run relationship among the variables. The results from cross-sectionally augmented autoregressive distributed lag (CS-ARDL) model reveal that climate change negatively affects agricultural production; on the other hand, renewable energy, human capital, and institutional quality affect positively agricultural production. Moreover, renewable energy utilization, human capital, and intuitional quality moderates the effect of carbon emission on agricultural production. In addition, a U-shaped relationship exists between financial development and agricultural production, suggesting that financial development improves agricultural production only after reaching a certain threshold. Hence, this study suggests that ASEAN-4 countries must adopt flexible financial and agricultural policies so that farmers would be benefitted and agricultural production can be increased.
    Matched MeSH terms: Climate Change*
  12. Fulltext Understanding human vulnerability to climate change: A global perspective on index validation for adaptation planning
    Birkmann J, Jamshed A, McMillan JM, Feldmeyer D, Totin E, Solecki W, et al.
    Sci Total Environ, 2022 Jan 10;803:150065.
    PMID: 34525713 DOI: 10.1016/j.scitotenv.2021.150065
    Climate change is a severe global threat. Research on climate change and vulnerability to natural hazards has made significant progress over the last decades. Most of the research has been devoted to improving the quality of climate information and hazard data, including exposure to specific phenomena, such as flooding or sea-level rise. Less attention has been given to the assessment of vulnerability and embedded social, economic and historical conditions that foster vulnerability of societies. A number of global vulnerability assessments based on indicators have been developed over the past years. Yet an essential question remains how to validate those assessments at the global scale. This paper examines different options to validate global vulnerability assessments in terms of their internal and external validity, focusing on two global vulnerability indicator systems used in the WorldRiskIndex and the INFORM index. The paper reviews these global index systems as best practices and at the same time presents new analysis and global results that show linkages between the level of vulnerability and disaster outcomes. Both the review and new analysis support each other and help to communicate the validity and the uncertainty of vulnerability assessments. Next to statistical validation methods, we discuss the importance of the appropriate link between indicators, data and the indicandum. We found that mortality per hazard event from floods, drought and storms is 15 times higher for countries ranked as highly vulnerable compared to those classified as low vulnerable. These findings highlight the different starting points of countries in their move towards climate resilient development. Priority should be given not just to those regions that are likely to face more severe climate hazards in the future but also to those confronted with high vulnerability already.
    Matched MeSH terms: Climate Change*
  13. Impact of climate change on biodiversity loss: global evidence
    Habibullah MS, Din BH, Tan SH, Zahid H
    Environ Sci Pollut Res Int, 2022 Jan;29(1):1073-1086.
    PMID: 34341937 DOI: 10.1007/s11356-021-15702-8
    The present study investigates the impact of climate change on biodiversity loss using global data consisting of 115 countries. In this study, we measure biodiversity loss using data on the total number of threatened species of amphibians, birds, fishes, mammals, mollusks, plants, and reptiles. The data were compiled from the Red List published by the International Union for Conservation of Nature (IUCN). For climate change variables, we have included temperature, precipitation, and the number of natural disaster occurrences. As for the control variable, we have considered governance indicator and the level of economic development. By employing ordinary least square with robust standard error and robust regression (M-estimation), our results suggest that all three climate change variables - temperature, precipitation, and the number of natural disasters occurrences - increase biodiversity loss. Higher economic development also impacted biodiversity loss positively. On the other hand, good governance such as the control of corruption, regulatory quality, and rule of law reduces biodiversity loss. Thus, practicing good governance, promoting conservation of the environment, and the control of greenhouse gasses would able to mitigate biodiversity loss.
    Matched MeSH terms: Climate Change*
  14. Fulltext Data-driven models for atmospheric air temperature forecasting at a continental climate region
    Alomar MK, Khaleel F, Aljumaily MM, Masood A, Razali SFM, AlSaadi MA, et al.
    PLoS One, 2022;17(11):e0277079.
    PMID: 36327280 DOI: 10.1371/journal.pone.0277079
    Atmospheric air temperature is the most crucial metrological parameter. Despite its influence on multiple fields such as hydrology, the environment, irrigation, and agriculture, this parameter describes climate change and global warming quite well. Thus, accurate and timely air temperature forecasting is essential because it provides more important information that can be relied on for future planning. In this study, four Data-Driven Approaches, Support Vector Regression (SVR), Regression Tree (RT), Quantile Regression Tree (QRT), ARIMA, Random Forest (RF), and Gradient Boosting Regression (GBR), have been applied to forecast short-, and mid-term air temperature (daily, and weekly) over North America under continental climatic conditions. The time-series data is relatively long (2000 to 2021), 70% of the data are used for model calibration (2000 to 2015), and the rest are used for validation. The autocorrelation and partial autocorrelation functions have been used to select the best input combination for the forecasting models. The quality of predicting models is evaluated using several statistical measures and graphical comparisons. For daily scale, the SVR has generated more accurate estimates than other models, Root Mean Square Error (RMSE = 3.592°C), Correlation Coefficient (R = 0.964), Mean Absolute Error (MAE = 2.745°C), and Thiels' U-statistics (U = 0.127). Besides, the study found that both RT and SVR performed very well in predicting weekly temperature. This study discovered that the duration of the employed data and its dispersion and volatility from month to month substantially influence the predictive models' efficacy. Furthermore, the second scenario is conducted using the randomization method to divide the data into training and testing phases. The study found the performance of the models in the second scenario to be much better than the first one, indicating that climate change affects the temperature pattern of the studied station. The findings offered technical support for generating high-resolution daily and weekly temperature forecasts using Data-Driven Methodologies.
    Matched MeSH terms: Climate Change*
  15. Fulltext Impacts of climate change and environmental degradation on children in Malaysia
    Sahani M, Othman H, Kwan SC, Juneng L, Ibrahim MF, Hod R, et al.
    Front Public Health, 2022;10:909779.
    PMID: 36311578 DOI: 10.3389/fpubh.2022.909779
    The impacts of climate change and degradation are increasingly felt in Malaysia. While everyone is vulnerable to these impacts, the health and wellbeing of children are disproportionately affected. We carried out a study composed of two major components. The first component is an environmental epidemiology study comprised of three sub-studies: (i) a global climate model (GCM) simulating specific health-sector climate indices; (ii) a time-series study to estimate the risk of childhood respiratory disease attributable to ambient air pollution; and (iii) a case-crossover study to identify the association between haze and under-five mortality in Malaysia. The GCM found that Malaysia has been experiencing increasing rainfall intensity over the years, leading to increased incidences of other weather-related events. The time-series study revealed that air quality has worsened, while air pollution and haze have been linked to an increased risk of hospitalization for respiratory diseases among children. Although no clear association between haze and under-five mortality was found in the case-crossover study, the lag patterns suggested that health effects could be more acute if haze occurred over a longer duration and at a higher intensity. The second component consists of three community surveys on marginalized children conducted (i) among the island community of Pulau Gaya, Sabah; (ii) among the indigenous Temiar tribe in Pos Kuala Mu, Perak; and (iii) among an urban poor community (B40) in PPR Sg. Bonus, Kuala Lumpur. The community surveys are cross-sectional studies employing a socio-ecological approach using a standardized questionnaire. The community surveys revealed how children adapt to climate change and environmental degradation. An integrated model was established that consolidates our overall research processes and demonstrates the crucial interconnections between environmental challenges exacerbated by climate change. It is recommended that Malaysian schools adopt a climate-smart approach to education to instill awareness of the impending climate change and its cascading impact on children's health from early school age.
    Matched MeSH terms: Climate Change*
  16. Interpretable and explainable AI (XAI) model for spatial drought prediction
    Dikshit A, Pradhan B
    Sci Total Environ, 2021 Dec 20;801:149797.
    PMID: 34467917 DOI: 10.1016/j.scitotenv.2021.149797
    Accurate prediction of any type of natural hazard is a challenging task. Of all the various hazards, drought prediction is challenging as it lacks a universal definition and is getting adverse with climate change impacting drought events both spatially and temporally. The problem becomes more complex as drought occurrence is dependent on a multitude of factors ranging from hydro-meteorological to climatic variables. A paradigm shift happened in this field when it was found that the inclusion of climatic variables in the data-driven prediction model improves the accuracy. However, this understanding has been primarily using statistical metrics used to measure the model accuracy. The present work tries to explore this finding using an explainable artificial intelligence (XAI) model. The explainable deep learning model development and comparative analysis were performed using known understandings drawn from physical-based models. The work also tries to explore how the model achieves specific results at different spatio-temporal intervals, enabling us to understand the local interactions among the predictors for different drought conditions and drought periods. The drought index used in the study is Standard Precipitation Index (SPI) at 12 month scales applied for five different regions in New South Wales, Australia, with the explainable algorithm being SHapley Additive exPlanations (SHAP). The conclusions drawn from SHAP plots depict the importance of climatic variables at a monthly scale and varying ranges of annual scale. We observe that the results obtained from SHAP align with the physical model interpretations, thus suggesting the need to add climatic variables as predictors in the prediction model.
    Matched MeSH terms: Climate Change
  17. Optimised and systematic suitable climate modelling confirms future longitudinal-trends for growing oil palm in Africa
    Paterson RRM
    J Environ Manage, 2021 Dec 15;300:113785.
    PMID: 34562818 DOI: 10.1016/j.jenvman.2021.113785
    Palms are iconic plants. Oil palms are very important economically and originate in Africa where they can act as a model for palms in general. The effect of future climate on the growth of oil palm will be very detrimental. Latitudinal migration of tropical crops to climate refuges may be impossible, and longitudinal migration has only been confirmed for oil palm, of all the tropical crops. The previous method to determine the longitudinal trend for oil palm used the longitudes of various countries in Africa and plotted these against the percentage suitable climate for growing oil palms in each country. An increasing longitudinal trend was observed from west to east. However, the longitudes of the countries were randomly distributed which may have introduced bias and the procedure was time consuming. The present report presents an optimised and systematic procedure that divided the regions, as presented on a map derived from a CLIMEX model, into ten equal sectors and the percentage suitable climates for growing oil palm were determined for each sector. This approach was quicker, systematic and straight forward and will be useful for management of oil palm plantations under climate change. The method confirmed and validated the trends reported in the original method although the suitability values were often lower and there was less spread of values around the trend. The values for the CSIRO MK3.0 and MIROC H models demonstrated considerable similarities to each other, contributing to validation of the method. The procedure of dividing maps equally into sectors derived from models, could be used for other crops, regions, or systems more generally, where the alternative may be a more superficial visual examination of the maps. Methods are required to mitigate the effects of climate change and stakeholders need to contribute more actively to the current climate debate with tangible actions.
    Matched MeSH terms: Climate Change
  18. Fulltext Testing role of green financing on climate change mitigation: Evidences from G7 and E7 countries
    Wu X, Sadiq M, Chien F, Ngo QT, Nguyen AT, Trinh TT
    Environ Sci Pollut Res Int, 2021 Dec;28(47):66736-66750.
    PMID: 34235703 DOI: 10.1007/s11356-021-15023-w
    The study estimates the long-run dynamics of a cleaner environment in promoting the gross domestic product of E7 and G7 countries. The recent study intends to estimate the climate change mitigation factor for a cleaner environment with the GDP of E7 countries and G7 countries from 2010 to 2018. For long-run estimation, second-generation panel data techniques including augmented Dickey-Fuller (ADF), Phillip-Peron technique and fully modified ordinary least square (FMOLS) techniques are applied to draw the long-run inference. The results of the study are robust with VECM technique. The outcomes of the study revealed that climate change mitigation indicators significantly affect the GDP of G7 countries than that of E7 countries. The GDP of both E7 and G7 countries is found depleting due to less clean environment. However, green financing techniques helps to clean the environment and reinforce the confidence of policymakers on the elevation of green economic growth in G7 and E7 countries. Furthermore, study results shown that a 1% rise in green financing index improves the environmental quality by 0.375% in G7 countries, while it purifies 0.3920% environment in E7 countries. There is a need to reduce environmental pollution, shift energy generation sources towards alternative, innovative and green sources.The study also provides different policy implications for the stakeholders guiding to actively promote financial hedging for green financing. So that climate change and envoirnmental pollution reduction could be achieved effectively. The novelty of the study lies in study framework.
    Matched MeSH terms: Climate Change*
  19. Fulltext A time-series prediction model of acute myocardial infarction in northern of Iran: the risk of climate change and religious mourning
    Sharif Nia H, Gorgulu O, Naghavi N, Froelicher ES, Fomani FK, Goudarzian AH, et al.
    BMC Cardiovasc Disord, 2021 11 23;21(1):563.
    PMID: 34814834 DOI: 10.1186/s12872-021-02372-0
    BACKGROUND: Although various studies have been conducted on the effects of seasonal climate changes or emotional variables on the risk of AMI, many of them have limitations to determine the predictable model. The currents study is conducted to assess the effects of meteorological and emotional variables on the incidence and epidemiological occurrence of acute myocardial infarction (AMI) in Sari (capital of Mazandaran, Iran) during 2011-2018.

    METHODS: In this study, a time series analysis was used to determine the variation of variables over time. All series were seasonally adjusted and Poisson regression analysis was performed. In the analysis of meteorological data and emotional distress due to religious mourning events, the best results were obtained by autoregressive moving average (ARMA) (5,5) model.

    RESULTS: It was determined that average temperature, sunshine, and rain variables had a significant effect on death. A total of 2375 AMI's were enrolled. Average temperate (°C) and sunshine hours a day (h/day) had a statistically significant relationship with the number of AMI's (β = 0.011, P = 0.014). For every extra degree of temperature increase, the risk of AMI rose [OR = 1.011 (95%CI 1.00, 1.02)]. For every extra hour of sunshine, a day a statistically significant increase [OR = 1.02 (95% CI 1.01, 1.04)] in AMI risk occurred (β = 0.025, P = 0.001). Religious mourning events increase the risk of AMI 1.05 times more. The other independent variables have no significant effects on AMI's (P > 0.05).

    CONCLUSION: Results demonstrate that sunshine hours and the average temperature had a significant effect on the risk of AMI. Moreover, emotional distress due to religious morning events increases AMI. More specific research on this topic is recommended.

    Matched MeSH terms: Climate Change*
  20. Impacts of droughts and floods on croplands and crop production in Southeast Asia - An application of Google Earth Engine
    Venkatappa M, Sasaki N, Han P, Abe I
    Sci Total Environ, 2021 Nov 15;795:148829.
    PMID: 34252779 DOI: 10.1016/j.scitotenv.2021.148829
    While droughts and floods have intensified in recent years, only a handful of studies have assessed their impacts on croplands and production in Southeast Asia. Here, we used the Google Earth Engine to assess the droughts and floods and their impacts on croplands and crop production over 40 years from 1980 to 2019. Using the Palmer Drought Severity Index (PDSI) as the basis for determining the drought and flood levels, and crop damage levels, crop production loss in both the Monsoon Climate Region (MCR) and the Equatorial Climate Region (ECR) of Southeast Asia was assessed over 47,192 grid points with 10 × 10-kilometer resolution. We found that rainfed crops were severely affected by droughts in the MCR and floods in the ECR. About 9.42 million ha and 3.72 million ha of cropland was damaged by droughts and floods, respectively. We estimated a total loss of 20.64 million tons of crop production between 2015 and 2019. Rainfed crops in Thailand, Cambodia, and Myanmar were strongly affected by droughts, whereas Indonesia, the Philippines, and Malaysia were more affected by floods over the same period. Accordingly, four levels of policy interventions were prioritized by considering the geolocated crop damage levels.
    Matched MeSH terms: Climate Change
Related Terms
Filters
Contact Us

Please provide feedback to Administrator (afdal@afpm.org.my)

External Links