As the US population continues to increase and age, there is an unmet need for dermatologic care; therefore, it important identify understand characteristics patterns of dermatologist workforce.To analyze longitudinal density urban-rural disparities using a standardized classification scheme.This study analyzed county-level data 1995 2013 from Area Health Resources File evaluate trends demographic environmental factors associated with geographic distribution dermatologists.Active physician...

Population change and environmental degradation have become two of the most pressing issues for sustainable development in contemporary world, while effect population aging on pro-environmental behavior remains controversial. In this paper, we examine effects individual through multilevel analyses cross-national data from 31 countries. Hierarchical linear models with random intercepts are employed to analyze data. The findings reveal a positive relationship between behavior. At level, older...

ABSTRACT Climate change has exerted tremendous disruptive impacts on the planet and human society. The United States is a major contributor to this crisis witnessed extreme weather events more frequently in recent years. To address issue, it critical understand how Americans climate change. Our study uses data from two national surveys administered 2022 2023 investigate topic. Descriptive statistics reveal that most are concerned about risk, recognize ramifications of events, agree...

This study examines the ways in which social capital influences people’s environmental concern China. Using data obtained from 2010 Chinese General Social Survey, we measure through networks and trust. We find that people think about act toward others influence they environment. The structural equation modeling results suggest one’s connections with others, including socializing relatives friends as well general networking, are significantly positively related to various dimensions of...

Abstract To what degree are Chinese citizens concerned about the seriousness of global warming and climate change (GWCC) key factors that shape their concern? Drawing theoretical insights from extant literature using recent data a national representative public survey (N = 3,748) provincial environmental economic statistics, this study, first its kind, examines variations determinants GWCC concern. Our show in China, compared to other countries, average concern is relatively low, varies...

Existing cross-national studies have identified that country-level economic and environmental factors can affect concern at the individual-level. However, we know little in regard to how these contextual their interaction with individual-level shape within countries. Using China as an example, examine three hypotheses: affluence hypothesis, degradation need contingency hypothesis. We measure dimensions using twelve indicators. The latent mean comparison multilevel structural equation...

Objective This article evaluates the extent to which economic affluence, ecological degradation, integration into world polity, and globalization each contributes change in environmental concern 82 countries across seven years. Method Using multivariate panel regression, I have analyzed a combined data set of four waves World Values Surveys three surveys from International Social Survey Program. Results Findings reveal that exposure degradation is positively related growing concern, whereas...

One of the most critical issue facing humanity today is climate change, as rising incidence extreme weather events has surpassed adaptive capacity human societies. A fundamental transformation energy system urgently needed to address this issue. To gain a better understanding how exposure and perceptions change influence support for expanding renewable energies, nationally representative survey was conducted in 2021, incorporating contextual data on cost billion-dollar disasters carbon...

Machine learning (ML) models can simulate flood risk by identifying critical non-linear relationships between damage locations and factors (FRFs). To explore it, Tampa Bay, Florida, is selected as a test site. The study's goal to identify dominant FRFs using historical data target variable, with 16 predictor variables. Five different ML such decision tree (DT), support vector machine (SVM), adaptive boosting (AdaBoost), extreme gradient (XGBoost), random forest (RF) were adopted. RF...