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This chapter addresses the growing need to analyze the relationship between COVID-19 vulnerability and disability status at the national scale in the US. It presents a quantitative study that seeks to determine whether US counties more vulnerable to the COVID-19 pandemic contain significantly higher percentages of people with disabilities (PwDs), in general, and socially disadvantaged PwDs (based on their ethnicity/race, biological sex, age poverty, and employment status), in particular.

Vulnerability to COVID-19 is measured using the COVID-19 Pandemic Vulnerability Index (PVI) model developed by the National Institute of Environmental Health Sciences, which integrates multiple variables into relevant indicators that are weighted and combined to formulate a county-level PVI score. These scores are linked to a wide range of disability-related variables from the 2019 American Community Survey five-year estimates. Statistical analyses are based on multivariable generalized estimating equations that extend the generalized linear model to account for spatial clustering.

US counties more vulnerable to the COVID-19 pandemic are characterized by significantly higher percentages of PwDs, when vaccination is considered in estimating the PVI. These counties also contain significantly higher percentages of ethnic/racial minority, female, below poverty, and unemployed PwDs, in multiple timeframes of the pandemic.

The findings provide important insights and new knowledge on the relationship between COVID-19 vulnerability and socially disadvantaged PwDs in the US. The county-level associations highlight the need for additional data and more detailed analysis to examine the differential impacts of this pandemic on PwDs, as well as formulate appropriate intervention strategies.

To investigate the association between subjective dimensions of socioeconomic status and psychological distress, paying particular attention to Latino subgroup differences.

We used data from the Latino sample (N = 2,554) of the National Latino and Asian American Study (NLAAS). For our main analyses, we conducted a series of weighted multivariable linear regressions.

The results showed that subjective social status was associated with reduced psychological distress.

There are several key study limitations that warrant consideration. Chiefly, data utilized were cross-sectional; thus, it is unclear whether subjective socioeconomic status (SES) precedes or follows psychological distress.

Overall, our study makes several contributions to the sociological study of mental health differentials among Latinos. We show the importance of the association between subjective SES indicators and psychological distress. We also demonstrate how the associations analyzed in this study varied by Latino subethnicity, which we argue is an important step to fully understand the different social processes associated with the mental health of different Latina/o groups.

The overall objective of this research was to elucidate the ecosystem of women’s health social enterprises (WHSEs) based in the United States. The Aim I was to conduct a secondary data analysis of a random national sample of non-profit WHSEs based in the United States regarding their characteristics and areas of intervention. Aim II was to conduct a qualitative assessment of a sample of WHSEs based in the United States regarding their perspectives on the ecosystem of WHSEs. Aim I utilized the GuideStar database and assessed enterprise size, geographic location, financial distress, health intervention area, and health activity category using descriptive statistics, statistical tests, and multivariable regression analysis via SPSS. Aim II utilized in-depth interviewing and grounded theory analysis via MAXQDA 2018 to identify novel themes and core categories while using an established framework for mapping social enterprise ecosystems as a scaffold.

Aim I findings suggest that WHSE activity is more predominant in the south region of the United States but not geographically concentrated around cities previously identified as social enterprise hubs. WHSEs take a comprehensive approach to women’s health, often simultaneously focusing on multiple areas of health interventions. Although most WHSEs demonstrate a risk for financial distress, very few exhibited severe risk. Risk for financial distress was not significantly associated with any of the measured enterprise characteristics. Aim II generated four core categories of findings that describe the ecosystem of WHSE: (1) comprehensive, community-based, and culturally adaptive care; (2) interdependent innovation in systems, finances, and communication; (3) interdisciplinary, cross-enterprise collaboration; and (4) women’s health as the foundation for family and population health. These findings are consistent with the three-failures theory for non-profit organizations, particularly that WHSEs address government failure by focusing on the unmet women’s health needs of the underserved populations (in contrast to the supply of services supported by the median voter) and address the market failure of over exclusion through strategies such as cross-subsidization and price discrimination. While WHSEs operate with levels of financial risk and are subject to the voluntary sector failure of philanthropic insufficiency, the data also show that they act to remediate other threats of voluntary failure.

Aim I findings highlight the importance of understanding financial performance of WHSEs. Also, lack of significant associations between our assessed enterprise characteristics and their financial risk suggests need for additional research to identify factors that influence financial performance of WHSE. Aim II findings show that WHSEs are currently engaged in complex care coordination and comprehensive biopsychosocial care for women and their families, suggesting that these enterprises may serve as a model for improving women’s health and health care. The community-oriented and interdisciplinary nature of WHSE as highlighted by our study may also serve as a unique approach for research and education purposes. Additional research on the ecosystem of WHSE is needed in order to better inform generalizability of our findings and to elucidate how WHSE interventions may be integrated into policies and practices to improve women’s health.

Football is a popular sport among young people across Africa, incited by the heavy presence of European football that has become central to youth cultures, everyday social routines, forms of consumption and opportunities for establishing social status. A growing body of evidence suggests increasing trends in harmful gambling behaviours in African youth, while the proliferation of football betting particularly remains a critical potential risk for negative mental health outcomes among young people in Sub-Saharan Africa. This chapter draws on original empirical data from a web-based cross-sectional survey to examine the prevalence estimates and associations of socio-demographic and behavioural factors with football betting among young adults attending university in Ghana. It draws on a multivariable logistic regression model to assess the associations with football betting. Our findings point not only to the growing salience of football betting among male demographics, but also the role of peer culture, alcohol and media as predominant sources of participants' initiation of football betting. Moreover, participants indicated the motive ‘to make money’ as their single major motivation, which raises the prospect that football betting is used as a means to mitigate the adverse effects of unemployment. Overall, the study points to a need for harm prevention strategies that align more closely with public health approaches focused on students, their families, their communities and their universities/schools.

This study is an attempt to estimate the output growth and total factor productivity growth (TFPG) in Indian manufacturing industry. Most of the developed nations have been facing economic depression in its output and employment growth frequently which led to several worldwide recessions and developing nations have also been affected by these. Our objective is to examine a possible way of mitigating economic recession in the light of Indian experience. In these connections we have tried to establish a link between TFPG and indicators of economic growth like export, GDP, employment, etc. We have computed TFPG of Indian manufacturing industry for last 30 years. On an average TFPG of Indian manufacturing industry has been found negative with a declining trend. Time series analysis of our study reveals that all the variables are stationary at first difference. They are also found to be co-integrated. On the basis of volumes of India's exports of manufacturing products in 2017, we have selected top 27 destination countries. More than 60% of Indian's manufacturing products were exported to these countries in this year. We have conducted panel data analysis to find the relation between TFPG and growth of India's export. The result shows that there has been a positive and significant relation between these two. This study also found that there has been a positive relation between growth of gross value added and employment growth in Indian manufacturing industry. So, TFPG may be a useful way to mitigate economic recession.

Using a GED-GARCH model to estimate monthly data from January 1990 to February 2022, we test whether gold acts as a hedge or safe haven asset in 10 countries. With a downturn of the stock market, gold can be viewed as a hedge and safe haven asset in the G7 countries. In the case of inflation, gold acts as a hedge and safe haven asset in the United States, United Kingdom, Canada, China, and Indonesia. For currency depreciation, oil price shock, economic policy uncertainty, and US volatility spillover, evidence finds that gold acts as a hedge and safe haven for all countries.

The objective of this study is to investigate how country risk, different political actions from the government and bureaucratic behavior influence the activities in industry supply chains (SCs) in emerging markets. The main objective of this study is to investigate the influence of these external stakeholders’ elements to the demand-side and supply-side drivers and barriers for improving competitiveness of Ready-Made Garment (RMG) industry in the way of analyzing supply chain. Considering the phenomenon of recent change in the RMG business environment and the competitiveness issues this study uses the principles of stakeholder and resource dependence theory and aims to find out some factors which influence to make an efficient supply chain for improving competitiveness. The RMG industry of Bangladesh is the case application of this study. Following a positivist paradigm, this study adopts a two phase sequential mixed-method research design consisting of qualitative and quantitative approaches. A tentative research model is developed first based on extensive literature review. Qualitative field study is then carried out to fine tune the initial research model. Findings from the qualitative method are also used to develop measures and instruments for the next phase of quantitative method. A survey is carried out with sample of top and middle level executives of different garment companies of Dhaka city in Bangladesh and the collected quantitative data are analyzed by partial least square-based structural equation modeling. The findings support eight hypotheses. From the analysis the external stakeholders’ elements like bureaucratic behavior and country risk have significant influence to the barriers. From the internal stakeholders’ point of view the manufacturers’ and buyers’ drivers have significant influence on the competitiveness. Therefore, stakeholders need to take proper action to reduce the barriers and increase the drivers, as the drivers have positive influence to improve competitiveness.

This study has both theoretical and practical contributions. This study represents an important contribution to the theory by integrating two theoretical perceptions to identify factors of the RMG industry’s SC that affect the competitiveness of the RMG industry. This research study contributes to the understanding of both external and internal stakeholders of national and international perspectives in the RMG (textile and clothing) business. It combines the insights of stakeholder and resource dependence theories along with the concept of the SC in improving effectiveness. In a practical sense, this study certainly contributes to the Bangladeshi RMG industry. In accordance with the desire of the RMG manufacturers, the research has shown that some influential constructs of the RMG industry’s SC affect the competitiveness of the RMG industry. The outcome of the study is useful for various stakeholders of the Bangladeshi RMG industry sector ranging from the government to various private organizations. The applications of this study are extendable through further adaptation in other industries and various geographic contexts.

Allocating budget optimally to marketing channels is an increasingly difficult venture. This difficulty is compounded by an increase in the number of marketing channels, a rise in siloed data between marketing technologies, and a decrease in individually identifiable data due to legislated privacy policies. The authors explore the rich attribution modeling literature and discuss the different model types and approaches previously used by practitioners and researchers. They also investigate the changing landscape of marketing attribution, discuss the advantages and disadvantages of different data handling approaches (i.e., aggregate vs. individualistic data), and present a research agenda for future attribution research.