Zhang Jianglin’s research while affiliated with Shenzhen Second People's Hospital and other places

Inadequate diet and nutritional quality are potentially correlated with an escalated risk of cardiac-related morbidity and mortality. A plethora of knowledge is available regarding the influence of heart-healthy dietary patterns in response to disability-adjusted life years (DALYs), yet little is known regarding the best approaches to adopt. In response, the present investigation aims to bridge this knowledge gap by implementing mathematical machine learning grey methodology to assess the degree of influence and the potential contributing factors in DALYs due to ischemic heart disease and stroke, in conjunction with the Hurwicz (Min-Max) criterion. The outcomes highlighted that a diet low in fruits is a potential contributor to IHD-related DALYS, whereas a diet low in vegetables is a more grounded contributor to stroke-related DALYs in Spain, among others. Moreover, the Hurwicz approach highlighted IHD to be more impacted due to dietary and nutritional factors than stroke. In conclusion, our investigation strongly supports a balanced diet and precision nutrition guidelines as a strategy for reducing cardiac-related diseases in the Spanish population. It is a public health primary consideration to build an ambiance that encourages, rather than hinders, compliance with cardioprotective dietary practices among all people.

Since the thrust of previous research investigations has been on people's willingness to get immunized against the COVID-19 infection, the underpinning principle of compliance has received very little attention. Addressing the possible drivers and mechanisms influencing vaccine acceptance may provide significant insights for limiting the pandemic. In response, we intend to investigate the influence of decision regret and the consequences of post-vaccination adverse effects on the inclination to undertake booster shots. An electronic survey that was self-administered was conducted in Rawalpindi, Pakistan. The questionnaire was completed by 1,369 participants, with a response rate of 41%. 1,343 of them (98.10%) had received both doses of the COVID-19 vaccination. Besides, the present research has also adopted a mediation model. Our findings demonstrate that unfavorable vaccination responses in healthcare workers significantly affect their likelihood of receiving booster shots. Interestingly, healthcare workers who had adverse experiences after being immunized were more prone to regret their prior immunization decisions, which in response affected their decision to get a booster shot. The motivation to receive the booster dosage and adverse post-vaccination responses were mediated by decision regret. The outcomes suggested indissociable connections between unfavorable vaccination responses, decision regret, and the likelihood of receiving a booster shot. To strengthen immunization acceptance intent and enhance the likelihood of receiving COVID-19 booster shots, it is recommended that awareness of these post-vaccination adverse events be extensively integrated into immunization awareness programs and policy measures supporting booster doses.

The present study empirically analyzes the role of eco-innovation in plummeting carbon dioxide (CO 2 ) emissions in conjunction with renewable energy usage, foreign direct investment, and trade openness for the states in G-7 from 1990 to 2019 in a mathematical and statistical context. Under the dynamical framework, the estimates of mathematical grey relational analyses indicate that eco-innovation holds a stronger degree of association with CO 2 emissions. Further, the estimates demonstrate that, compared to the other G-7 states, Japan is the country where eco-innovation is a more striking variable. However, renewable energy utilization seems weaker in Japan, which necessitates adopting renewable energy to curb carbon emissions in the region. Statistically, the odds ratio illustrates a similar pattern, demonstrating that the odds of occurrence for eco-innovation are much stronger in reducing the rising levels of carbon emissions within the G-7 states. Moreover, trade openness and foreign direct investment were revealed to be the leading contributors to carbon emissions in Germany and Canada, respectively, whilst appearing to be significant variables in lowering emissions in the United States and the United Kingdom. The outcomes of this investigation offer significant perspectives for policymakers in formulating holistic and environmentally friendly policies by embracing eco-innovation as a potentially significant component for sustainable economic expansion and environmental health.

Environmental degradation has been identified as a major worldwide concern in recent decades, with CO 2 emissions considered as one of the primary drivers of this catastrophe. This study creatively analyzes the underlying impact of wind and solar energy generation, economic development, fossil fuel consumption on CO 2 emissions to mitigate the environmental degradation in the world’s top three largest energy consumers and CO 2 emitters nations namely, China, India, and the USA. To investigate the integrated impact of CO 2 emission, a grey relational analysis (GRA) technique is adopted for the year 1990–2017. The Grey technique for order of preference by similarity to ideal solution (G-TOPSIS) technique was employed for further optimization by prioritizing the explanatory factors that have potential influence on CO 2 emissions in the selected nations. The outcomes through the GRA technique discovered that India is a major contributor of carbon emission caused by economic development, and China appeared to be the more afflicted nation for raising its carbon emissions owing to fossil fuel consumption. Whereas, the generation of solar and wind energy are grounded factors in the reduction of carbon emissions for China and the USA. In addition, the generation of wind energy showed a considerable impact in the reduction of CO 2 emissions, based on the G-TOPSIS analysis. This suggests that reducing CO 2 emissions would require a compendious transition from nonrenewable to renewable resources, while the United States and China appear to be on a more promising direction to environmental sustainability than India. As a growing renewable energy pioneer, India should increase the utilization of minimal carbon sources of energy in its electricity grid while limiting its reliance on fossil fuels. The findings of the study potentially aid governments and policymakers in making better decisions and investments to mitigate CO 2 emissions while fostering a more environmentally friendly atmosphere.

The health industry is amongst the most affected systems in terms of multiobjective decision-making, rendering the final solution, vulnerable to errors; however, multicriteria decision analysis (MDCA) emerges as a supportive tool for the process of decision-making. Therefore, the present study seeks to offer an MCDA framework for assessing and identifying the potential influence of socioeconomic risk factors on noncommunicable disease mortality. We adopted a subjective approach of grey-based Step-wise Weight Assessment Ratio Analysis (SWARA) and COmplex PRoportional Assessment (COPRAS) approach to calculate weights of parameters and criteria, respectively, and then rank them based on their degree of significance. The findings reveal that CRD mortality is potentially affected by the selected socioeconomic risk variables followed by IHD and cancer. Implementing MCDA techniques in the present study will assist the public health practitioners and policymakers in drawing decisions on the best strategy to reduce CRD mortality, which contributes significantly to raising overall mortality.

Background: Measuring the potential socioeconomic factors of cardiac mortality is fundamental to identifying treatments, setting priorities, and effectively allocating resources to minimize disease burden. The study sought to present a methodology that explores the connections between urbanization, population growth, human development index (HDI), access to energy, unemployment, and cardiovascular disease (CVD) mortality within the South Asian Association for Regional Cooperation (SAARC) nations to mitigate the cardiac disease burden. Methods: This investigation uses multiple-criteria decision-making methodologies to analyze data between 2001 and 2017 commencing with a mathematical grey incidence analysis (GIA) methodology to estimate weights and rank nations based on CVD mortality. Then, utilizing the conservative min-max model approach, we sought to determine which country contributes the most to CVD mortality among all South Asian nations. The grey preference by similarity to ideal solution (G-TOPSIS) method is adopted for further optimization by prioritizing the selected factors that have the greatest influence on CVD mortality. Results: The estimated statistic highlights that, among SAARC nations, Pakistan has a significant proportion of the disease burden attributable to cardiac events. In addition, HDI showed a significant contribution in the reduction of CVD mortality, whereas unemployment showed a significant contribution in the rise of CVD mortality among all selected variables. Conclusions: This investigation may facilitate researchers with a multiple-criteria decision-making roadmap to help them enhance the quality of their studies and their understanding of how to use multiple-criteria decision-making techniques to evaluate and prioritize the influencing factors of disease mortality in healthcare research. Further, the study outcomes provide additional practical knowledge for appropriate policy solutions.

It was highlighted that in the original article [1] under the section Relative growth rate (RGR) and doubling time (Dt) analysis, the equations erroneously contained some red text. The original article has been updated.

Background The study aims to predict and assess cardiovascular disease (CVD) patterns in highly affected countries such as Pakistan, India, China, Kenya, the USA, and Sweden. The data for CVD deaths was gathered from 2005 to 2019. Methods We utilized non-homogenous discrete grey model (NDGM) to predict growth of cardiovascular deaths in selected countries. We take this process a step further by utilizing novel Synthetic Relative Growth Rate (RGR) and Synthetic Doubling Time (Dt) model to assess how many years it takes to reduce the cardiovascular deaths double in numbers. Results The results reveal that the USA and China may lead in terms of raising its number of deaths caused by CVDs till 2027. However, doubling time model suggests that USA may require 2.3 years in reducing the cardiovascular deaths. Conclusions This study is significant for the policymakers and health practitioners to ensure the execution of CVD prevention measures to overcome the growing burden of CVD deaths.