Global Transitions最新文献

Context

Methods

Findings

Conclusions

Introduction

Methods

Results

Conclusion

Purposes

Methods

Findings

Conclusions

Background

This study aimed to evaluate the longitudinal relationships between living alone, being childless, and six mental health indicators and mortality in older adults in Thailand between 2015 and 2020.

Methods

We examined prospective cohort data from the Health, Aging and Retirement in Thailand (HART) study, which included participants 45 years of age and older (N = 2863) from three successive waves in 2015, 2017, and 2020. Mental health indicators were assessed by self-report. We used Generalized Estimating Equations analysis (GEE) to evaluate the longitudinal relationships between measures of living alone, childlessness and six mental health indicators and mortality.

Results

The proportion of living alone was 6.3 % and childlessness 9.9 % in 2015, while living alone only was 3.9 %, childlessness only 7.5 % and both living alone and childlessness 2.4 % in 2015. In the adjusted model, living alone only was among men positively associated with depressive symptoms, loneliness, poor quality of life and mortality, and among women only positively associated with poor quality of life. Childlessness only was among women positively associated with depressive symptoms, insomnia symptoms, loneliness, poor quality of life, poor self-rated mental health, and mortality, and among men with depressive symptoms, loneliness, poor quality of life and poor self-rated mental health. Both living alone and childlessness was among men associated with four mental health indicators (depressive symptoms, insomnia symptoms, loneliness, and poor quality of life), and among women two mental health indicators (loneliness and poor quality of life), all with higher odds ratios than in living alone only and childlessness only.

Conclusions

Living alone only, childlessness only and/or both living alone and childlessness were associated with several poor mental health indicators and/or mortality. Enhanced screening and management of living alone and being childless may improve mental health in Thailand.

Background

Lesotho has made significant strides towards universal health coverage and yet a significant proportion of the population has difficulty accessing health care services due to mountainous terrain and long travel times to nearest health facility. There have been previous studies that utilized Geographical Information Systems (GIS) to assess access to healthcare and to identify optimal locations for placement of new health facilities, though never in Lesotho.

Methods

The authors employed a mixed-methods design. Qualitative research consisting of semi-structured interviews and focus group discussions was used to gain a deep understanding of the problem with access to healthcare and to allow for the perspectives of the people of Lesotho to guide decision-making about placement of new healthcare facilities. GIS analysis was done using ArcGIS Pro v. 2.3 software and modern satellite imagery to map current access to healthcare facilities and create site recommendations for new healthcare facilities.

Results

Qualitative research revealed that walking was the primary mode of transport to healthcare facilities and that distance was the crucial barrier in limiting access to care. Decentralization in decision-making was identified as an important element in health policy decisions and study participants recommended placing health facilities centrally in large villages. GIS analysis identified that 77.7 % of the population was currently within 3-h walking distance to nearest health facility and that the addition of fifty new healthcare facilities would increase that proportion to 90.0 %.

Conclusion

This study mapped current access to care in Lesotho in rural and urban areas. It also provided an objective strategy for identifying the location of new healthcare facilities while incorporating the voices of the people of Lesotho in the process. The findings can be used to assist policymakers, and the methodology can be employed in the allocation of other public-service facilities in different countries or regions.

Knowledge about upcoming sustainability challenges is crucial to tackle them by political incentives, not at least to reach the United Nations’ 17 Sustainable Development Goals (SDGs). SDGs are multi-dimensional and require detail beyond an aggregate household approach to assess income inequality and other differences across households in transformative processes. Incorporating these aspects, we develop an SDG indicator framework for dynamic Computable General Equilibrium Models with a total of 68 endogenous indicators related to 15 SDGs. This enables a more differentiated assessment of the SDGs in forward looking analysis compared to existing approaches, by considering additional SDG indicators and household level detail based on micro-simulation. We apply the indicator framework in a global analysis of 3 Shared Socioeconomic Pathways (SSPs) until 2050 with a focus on selected low- and lower-middle income countries from different continents. The analysis finds sustainability gaps by 2030 and 2050 for all focus countries, especially in the environmental domain. In none of the analyzed SSPs, all indicators develop in the desired direction, underlining trade-off among and within SDGs, but also across the SSPs. Based on household detail, we find increasing inequality over time for several indicators regardless of developments at average aggregate household level, pointing at the need for targeted redistribution and compensation policies. These results highlight the importance of including distributional aspects and disaggregated data in policy and socioeconomic development studies.

Sulphur dioxide (SO₂) is a hazardous air pollutant, which is mostly emitted from burning of fossil fuels, and has an adverse impact on the human health and ecosystem functioning. The COVID-19 natural anthropause (lockdown) provides a great opportunity to understand the changes in SO₂ pollution across the globe, as there was a temporary standstill for most human activities. Therefore, we analyse the changes in global SO₂ pollution during lockdown compared to pre-lockdown and identify its hotspots driven by human activities using satellite measurements, reanalysis data and emission inventory. We observe a decline in SO₂ pollution of about 2.21 % in its global average, −21.05 % in Indo-Gangatic Plain, −16 % in East China, −7.67 % in East United States of America, −3.99 % in Western Europe and −3.85 % in Middle East owing to the halt in human activities such as industrial and transport operations, as found from the emissions inventory. There are point and aerial hotspots of SO₂ pollution across the globe (e.g. cities or industrial units), which also show a decrease (20–30 %) in SO₂ pollution during the anthropause. Fossil fuel burning in thermal power plants is a major source of SO₂ pollution, and it has declined notably (1–12 %) during the lockdown in the major coal consuming countries such as the United States, China, Japan, Canada, Brazil, Australia, France, Germany, Spain, Italy and the United Kingdom. Therefore, lockdown provides a clear understanding of global human-driven hotspots of SO₂ pollution and their changes, which would help us to make better and effective air pollution mitigation strategies.