An Integrated Analysis of Social, Economic, and Environmental Indicators' Effects on Public Health and Health Inequality Globally: From the Perspective of Vulnerability

The impact of temperature changes on the health vulnerability of migrant workers: an empirical study based on the China family panel studies

Introduction

Migrant workers constitute a significant portion of China's workforce, and their health directly affects labor supply and economic stability. Health vulnerability plays a crucial role in shaping the well-being of migrant workers, yet its determinants, particularly the impact of temperature change, remain underexplored. This study, based on the socio-ecological model, investigates how temperature variations influence the health vulnerability of migrant workers in China.

Methods

Using data from 2020, this study quantifies health vulnerability and examines the impact of temperature fluctuations across different seasons. Robustness checks, including dependent variable substitutions and model modifications, ensure the reliability of the findings. Furthermore, a mechanism analysis is conducted to explore the underlying pathways through which temperature change affects health vulnerability.

Results

The findings reveal that rising temperatures in spring, summer, and winter significantly exacerbate the health vulnerability of migrant workers, while increasing autumn temperatures mitigate it. Mechanism analysis identifies heightened psychological burden as a key channel through which temperature change worsens health vulnerability. Additionally, generational differences emerge: older migrant workers are more adversely affected by elevated spring temperatures, whereas younger workers exhibit greater sensitivity to rising summer temperatures.

Discussion

These results underscore the necessity of targeted health interventions and adaptive labor protection policies. By highlighting the seasonal and generational disparities in the effects of temperature change, this study offers theoretical and empirical support for enhancing the resilience of migrant workers to climate variations. The findings provide valuable insights for policymakers in designing strategies to safeguard the health and stability of the migrant workforce.

Evaluating the Governance Ability of Urban Public Health Using EM-AHP-TOPSIS Method: A Case Study in China

Background

Evaluating the governance capacity of urban public health is the key to improving the level of urban public health. We aimed to evaluate the governance ability of urban public health.

Methods

An index system of governance ability of urban public health was established. The governance ability of urban public health was evaluated, and major constraints against the ability improvement were analyzed through the EM (Entropy Method)-AHP (Analytic Hierarchy Process)-TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) model and data of urban agglomeration in Yangtze River Delta, China in 2023.

Results

Shanghai, Nanjing, Hangzhou, Suzhou, and Ningbo rank top 5 in terms of governance ability of public health, and they are in the first echelon. Hefei, Yancheng, Wuxi, Taizhou and Shaoxing rank 6-10, and they are in the second echelon. The remaining 17 cities are in the third echelon. Major sources of governance ability of urban public health and major factors that decrease governance ability are Medical Facility (A12), Health Improvement (A33), Medical Staff (A13), Government Ability (A11), and Health Loss (A34). For urban agglomeration in Yangtze River Delta, China, public health foundations, environmental exposure risks, public health performance, and public health emergencies all can influence the governance ability of public health.

Conclusion

Accurate evaluation of the governance ability of urban public health can provide guidance and policy propositions to improve the governance system of public health and improve the emergency coordination ability of the government.

Representation of Environmental Concepts Associated with Health Impacts in Computer Standardized Clinical Terminologies

OBJECTIVE

To evaluate the representation of environmental concepts associated with health impacts in standardized clinical terminologies.

METHODS

This study used a descriptive approach with methods informed by a procedural framework for standardized clinical terminology mapping. The United Nations Global Indicator Framework for the Sustainable Development Goals and Targets was used as the source document for concept extraction. The target terminologies were the Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) and the International Classification for Nursing Practice (ICNP). Manual and automated mapping methods were utilized. The lists of candidate matches were reviewed and iterated until a final mapping match list was achieved.

RESULTS

A total of 119 concepts with 133 mapping matches were added to the final SNOMED CT list. Fifty-three (39.8%) were direct matches, 37 (27.8%) were narrower than matches, 35 (26.3%) were broader than matches, and 8 (6%) had no matches. A total of 26 concepts with 27 matches were added to the final ICNP list. Eight (29.6%) were direct matches, 4 (14.8%) were narrower than, 7 (25.9%) were broader than, and 8 (29.6%) were no matches.

CONCLUSION

Following this evaluation, both strengths and gaps were identified. Gaps in terminology representation included concepts related to cost expenditures, affordability, community engagement, water, air and sanitation. The inclusion of these concepts is necessary to advance the clinical reporting of these environmental and sustainability indicators. As environmental concepts encoded in standardized terminologies expand, additional insights into data and health conditions, research, education, and policy-level decision-making will be identified.

Potential Epidemic Vulnerability and Socioepidemiological Profile of SARS-CoV2 in the Brazilian Northeast Region

Background: COVID-19 is a significant public health problem that can have a negative impact, especially in vulnerable regions. Objective: This study aimed to provide evidence that could positively influence coping with COVID-19 based on the relationship between the potential epidemic vulnerability index (PEVI) and socioepidemiological variables. This could be used as a decision-making tool for the planning of preventive initiatives in regions with relevant vulnerability indices for the spread of SARS-CoV-2. Methodology: We performed a cross-sectional study, with the analysis of the population characteristics of COVID-19 cases associated with neighborhoods’ PEVIs in the conurbation region of Crajubar, northeastern Brazil, through the mapping of socioeconomic–demographic factors and spatial autocorrelation. Results: The PEVI distribution indicated low vulnerability in areas with high real estate and commercial value; as communities moved away from these areas, the vulnerability levels increased. As for the number of cases, three of the five neighborhoods with a high–high autocorrelation, and some other neighborhoods showed a bivariate spatial correlation with a low–low PEVI but also high–low with indicators that make up the PEVI, representing areas that could be protected by public health measures to prevent increases in COVID-19 cases. Conclusions: The impact of the PEVI revealed areas that could be targeted by public policies to decrease the occurrence of COVID-19.

Is Economic Growth Good for Population Health? A Critical Review

A large multidisciplinary literature discusses the relationship between economic growth and population health. The idea that economic growth is good for societies has inspired extensive academic debate, but conclusions have been mixed. To help shed light on the subject, this paper focuses on opportunities for consensus in this large literature. Much scholarship finds that the health-growth relationship varies according to (1) which aspect of "health" is under consideration, (2) shape (e.g., positive linear or logarithmic), (3) issues of timing (e.g., growth over the short or long term), (4) a focus on health inequalities as opposed to population averages, and (5) multivariable relationships with additional factors. After reflecting upon these findings, I propose that economic growth promotes health in some respects, for some countries, and in conjunction with other life-supporting priorities, but does not by itself improve population health generally speaking. I then argue there is already wide, interdisciplinary consensus to support this stance. Moreover, policies focusing exclusively on economic growth threaten harm to both population health and growth, which is to say that political dynamics are also implicated. Yet multivariable approaches can help clarify the bigger picture of how growth relates to health. For moving this literature forward, the best opportunities may involve the simultaneous analysis of multiple factors. The recognition of consensus around these issues would be welcome, and timely.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42650-023-00072-y.

"Digital Dividend" or "Digital Divide": What Role Does the Internet Play in the Health Inequalities among Chinese Residents?

With the vigorous development of the medical industry in China, residents' health has been significantly improved. However, along with the income gap, urban-rural gap, and healthcare resource gap caused by economic development, health inequality has become a fundamental barrier to the promotion of residents' health. The popularity of the Internet has helped close the gap to some extent, but it also has drawbacks. Using data from the China Family Panel Studies (CFPS) from 2014 to 2018, we evaluated the effects of Internet usage on health disparities among residents using fixed effect models, mediation effect models, and other methodologies. The findings indicate that Internet usage can help to minimize health inequality since it lowers income inequality, promotes health consciousness, and reduces depression. Furthermore, Internet usage plays a greater role on the health improvement of the middle-aged, the elderly, urban residents, and females. Although the Internet has brought "digital dividends" in general, the Internet usage rates among different groups also reveal that there is a clear "digital gap" among rural residents, elderly groups, and low-income groups. These results have significant implications for promoting healthcare equality.

Food and housing security at a US Hispanic-Serving Institution: An examination before and during the COVID-19 pandemic

University students occupy a socially marginal position and therefore are often underserved by academic and service institutions. This article analyzes food and housing security among students at The University of Texas at El Paso, a Hispanic-Serving Institution located in the U.S.-Mexico Border region. Findings of a sample of n = 7,633 university students are presented in the first cross-sectional, two-year food and housing security study on campus administered via platform Campus Labs Baseline. The first sample in 2019 consisted of n = 2,615 students representing 10.4% of student enrollment (25,177 total 2019 enrollment), and the second sample in 2020 was n = 5,018 representing 20.2% of student enrollment (24,879 total 2020 enrollment). To measure food security, the six-item short form of the U.S. Department of Agriculture (USDA) Household Food Security Survey Module was used. To document housing security, we created questions informed by student input. In this study, survey results are reported, and tests are conducted to assess the relationships between various student characteristics and food and housing security. Student characteristics significantly impacting food and housing security are probed further using data visualizations and subpopulation analysis with a focus on analyzing factors impacted by the COVID-19 pandemic. Results indicate that employment status, consistent employment status, hours per week, academic level, number of dependents, and gender are all factors associated with food security during the pandemic but not prior to the pandemic. Other factors, including, college affiliation, ethnicity/race, having any dependents and being head of household, living alone, mode of campus transportation and mode of the transportation, household income, and age, all were associated with food security in both academic years. Using these results, a critical analysis of past interventions addressing food and housing security is presented with a focus on changes made during the pandemic. Recommendations are made for further data-driven interventions and future steps.