RESUMO
BACKGROUND AND OBJECTIVES: Substance use disorders (SUD) are a major public health concern in the United States. This study examined racial/ethnic and state-level disparities in SUD mortality in the United States from 2000 to 2019. METHODS: Age-standardized mortality rates for SUD were obtained for 5 racial/ethnic groups (White respondents, Black respondents, Latino, Asian-Pacific Islander [API], American Indian/Alaska Native [AIAN]) by state and sex from 2000 to 2019. Joinpoint regression analysis was used to model temporal trends overall and by demographic factors. RESULTS: From 2000 to 2019, the overall mortality rate increased from 8.0 to 28.8 deaths per 100,000 population across all groups. AIANs had the highest mortality in 2019 (57.8 per 100,000), followed by Black respondents, White respondents, Latinos, and APIs. Significant increases occurred across all racial/ethnic groups, with the greatest average annual percentage change (AAPC2000-2019) among White respondents (6.7%; 95% confidence interval [CI]: 6.2%-7.3%), APIs (6.0%, 95% CI: 5.6%-6.2%), and AIANs (5.9%, 95% CI: 5.6%-6.2%). Mortality rates increased more rapidly for females than males among White respondents, AIANs, Black respondents, and Latinos. Substantial state-level variation emerged, with the highest mortality rates in 2019 seen in West Virginia, the District of Columbia, Delaware, Ohio, and Pennsylvania. DISCUSSION AND CONCLUSIONS: Racial/ethnic and geographic disparities in SUD mortality have widened significantly from 2000 to 2019, highlighting priority areas for prevention efforts. SCIENTIFIC SIGNIFICANCE: This study provides detailed insights into long-term trends in racial, ethnic, and geographic disparities in SUD mortality across the United States, informing targeted prevention and intervention strategies.
RESUMO
The transition to a Circular Economy (CE) is rapidly gaining ground across countries and industries. It is the means of achieving more sustainable development by adopting innovative environmentally friendly strategies and saving primary resources. There are several studies indicating the increasing public and corporate interest in the CE but still remain limited in terms of the multitude and utilization of social media data. This work aims to shed light on the most common topics discussed on the YouTube platform, related to the CE. For this reason, we selected 17 videos including the term "Circular Economy" since these have been the most relevant with a sufficient number of comments and views. The model identified two main topics referring to "Sustainable industry and environmental responsibility" and "Circular Economy and resource management" which is a strong indicator of the people's interest in the utilization of resources alongside industrial and corporate activities. The two-topic configuration presented the highest coherence score; however, five and ten-topic configurations have been deployed since there was no extreme differentiation in the model's performance, which could provide more detailed insights. This work's innovation lies in utilizing Machine Learning techniques and social media data to unravel CE's debates.