Decomposition analysis of electricity generation on carbon dioxide emissions in Ghana

This study analyses the factors driving CO2 emissions from electricity generation in Ghana from 1990 to 2020. Employing Logarithmic Mean Divisia Index (LMDI) and Autoregressive Distributed Lag (ARDL) techniques, the research decomposes electricity generation into different factors and assesses their impact on CO2 emissions, considering both short and long-run effects. The LMDI analysis reveals that the total CO2 emissions from electricity generation amount to 3.33%, with all factors contributing positively in each subperiod. Notably, fossil fuel intensity, production, and transformation factors exhibit substantial contributions of about 1.16%, 0.49%, and 0.48%, respectively. Contrastingly, the ARDL results highlight that only electricity intensity and production factors significantly increase CO2 emissions by about 0.20% and 0.09% (0.38% and 0.10%) in the short-run (long-run), while other factors contribute to a reduction in electricity generation emissions. Overall, we conclude that electricity intensity and production factors are the primary drivers of CO2 emissions from electricity generation in Ghana. Nevertheless, effective measures to address all decomposition factors is crucial for effective mitigation of electricity generation CO2 emissions.

Impact of asset intensity and other energy-associated CO2 emissions drivers in the Nigerian manufacturing sector: A firm-level decomposition (LMDI) analysis

The study considered the impacts of asset intensity and other energy-associated CO 2 emissions drivers in the Nigerian manufacturing sector from 2010 to 2020. The Logarithmic Mean Divisia Index (LMDI) was used to explore the driving factors of CO 2 emissions: asset intensity, economic output, economic structure, energy intensity, energy mix, and carbon emission coefficient. From the results, the CO 2 emissions decreased from 7.49 MtCO 2 in 2010 to 3.22 MtCO 2 in 2020. Furthermore, among the emissions drivers, the energy mix effect increased CO 2 emissions by 0.50 MtCO 2 , followed by asset intensity (0.29 MtCO 2 ) and economic structure (0.11 MtCO 2 ) . The energy intensity, economic output, and emission coefficient effects inhibited CO 2 emissions by -4.64 MtCO 2 , -0.42 MtCO 2 , and -0.01 MtCO 2 respectively. The contribution of the subsectors' emissions shows that the Other Manufacturing subsector emitted 14.62 MtCO 2 , while Chemical and Pharmaceutical emitted 14.61 MtCO 2 , Food, Beverages and Tobacco, 7.55 MtCO 2 , Textile, Apparel, and Footwear, 6.63 MtCO 2 , Basic Metal and Iron and Steel, 5.15 MtCO 2 , Plastic and Rubber Products, 2.99 MtCO 2 , Agro-Allied, 2.71 MtCO 2 , Oil Refining, 2.01 MtCO 2 , and Pulp and Paper Products, 1.76 MtCO 2 . The results indicated that the effect of asset intensity on emission growth is significant and should not be overlooked. Likewise, the effects of CO 2 emission drivers were found to impact differently across the subsectors. The latter suggests that firm-specific indicators in the respective subsectors should be one of the primacies during policy development since the driving factors of CO 2 emissions fluctuate across the subsectors.

Rural-urban inequalities in health care utilization in Bhutan: a decomposition analysis

BACKGROUND AND OBJECTIVE

On the trajectory towards universal health coverage in Bhutan, health equity requires policy attention as significant disparities exist between urban and rural health outcomes. This paper examines health services utilization patterns, inequalities and their socio-economic determinants in rural and urban areas and decomposes the factors behind these differences.

METHODS

We used the Bhutan Living Standard Survey 2017 to profile health services utilization patterns and equalities. We employed two different decomposition analyses: decomposition of mean differences in utilization using the Oaxaca-Blinder decomposition framework and differences in the income-related distribution in utilization using recentered influence function regressions between rural and urban areas.

RESULTS

Significant differences exist in the type of outpatient services used by the rural and urban population groups, with those living in rural areas having 3.4 times higher odds of using primary health centers compared to outpatient hospital care. We find that the use of primary health care is pro-poor and that outpatient hospital resources is concentrated among the more affluent section of the population, with this observed inequality consistent across settings but more severe in rural areas. The rural-urban gap in utilization is primarily driven by income and residence in the eastern region, while income-related inequality in utilization is influenced, aside from income, by residence in the central region, household size, and marriage and employment status of the household head. We do not find evidence of significant mean differences in overall utilization or inequality in utilization of inpatient health care services.

CONCLUSIONS

While the differences in average contacts with health services are insignificant, there are prominent differences in the level of services availed and the associated inequality among rural and urban settings in Bhutan. Besides, while there are obvious overlaps, factors influencing income-related inequality are not necessarily the same as those driving the utilization gaps. Cognizance of these differences may lead to better informed, targeted, and potentially more effective future research and policies for universal health coverage.

Cause-Specific Mortality and Racial Differentials in Life Expectancy, Chicago 2018-2019

BACKGROUND

In Chicago in 2018, the average life expectancy (ALE) for NH Blacks was 71.5 years, 9.1 fewer years than for NH Whites (80.6 years). Inasmuch as some causes of death are increasingly recognized products of structural racism, in urban areas, such causes may have potential for reducing racial inequities through public health intervention. Our purpose is to allocate racial inequities in ALE in Chicago to differentials in cause-specific mortality.

METHODS

Using multiple decrement processes and decomposition analysis, we examine cause-specific mortality in Chicago to determine the causes of death that contribute to the gap in life expectancy between NH Blacks and NH Whites.

RESULTS

Among females, the racial difference in ALE was 8.21 years; for males, it was 10.53 years. We find that cancer and heart disease mortality account for 3.03 years or 36% of the racial gap in average life expectancy among females. Differences in homicide and heart disease mortality rates comprised over 45% of the disparity among males.

CONCLUSIONS

Strategies for improving inequities in life expectancy should account for differences between males and females in cause-specific mortality rates. In urban areas with high levels of segregation, reducing inequities in ALE may be possible by dramatically reducing mortality rates from some causes.

CONTRIBUTION

This paper illustrates the state of inequities in ALE between NH Blacks and NH Whites in Chicago for the period just prior to the onset of the COVID-19 pandemic, using a well-established method of decomposing mortality differentials for sub-populations.

Racial Inequities in the Control of Hypertension and the Explanatory Role of Residential Segregation: a Decomposition Analysis in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil)

The mechanisms underlying racial inequities in uncontrolled hypertension have been limited to individual factors. We investigated racial inequities in uncontrolled hypertension and the explanatory role of economic segregation in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). All 3897 baseline participants with hypertension (2008-2010) were included. Uncontrolled hypertension (SBP ≥ 140 mmHg or DBP ≥ 90 mmHg), self-reported race (White/Brown/Black people), and neighborhood economic segregation (low/medium/high) were analyzed cross-sectionally. We used decomposition analysis, which describes how much a disparity would change (disparity reduction; explained portion) and remain (disparity residual; unexplained portion) upon removing racial differences in economic segregation (i.e., if Black people had the distribution of segregation of White people, how much we would expect uncontrolled hypertension to decrease among Black people). Age- and gender-adjusted prevalence of uncontrolled hypertension (39.0%, 52.6%, and 54.2% for White, Brown, and Black participants, respectively) remained higher for Black and Brown vs White participants, regardless of economic segregation. Uncontrolled hypertension showed a dose-response pattern with increasing segregation levels for White but not for Black and Brown participants. After adjusting for age, gender, education, and study center, unexplained portion (disparity residual) of race on uncontrolled hypertension was 18.2% (95% CI 13.4%; 22.9%) for Black vs White participants and 12.6% (8.2%; 17.1%) for Brown vs White participants. However, explained portion (disparity reduction) through economic segregation was - 2.1% (- 5.1%; 1.3%) for Black vs White and 0.5% (- 1.7%; 2.8%) for Brown vs White participants. Although uncontrolled hypertension was greater for Black and Brown vs White people, racial inequities in uncontrolled hypertension were not explained by economic segregation.

Cause-of-Death Determinants of Lifespan Inequality

We propose a novel decomposition approach that breaks down the levels and trends of lifespan inequality as the sum of cause-of-death contributions. The suggested method shows whether the levels and changes in lifespan inequality are attributable to the levels and changes in (1) the extent of inequality in the cause-specific age-at-death distribution (the "Inequality" component), (2) the total share of deaths attributable to each cause (the "Proportion" component), or (3) the cause-specific mean age at death (the "Mean" component). This so-called Inequality-Proportion-Mean (or IPM) method is applied to 10 low-mortality countries in Europe. Our findings suggest that the most prevalent causes of death (in our setting, "circulatory system" and "neoplasms") do not necessarily contribute the most to overall levels of lifespan inequality. In fact, "perinatal and congenital" causes are the strongest drivers of lifespan inequality declines. The contribution of the IPM components to changes in lifespan inequality varies considerably across causes, genders, and countries. Among the three components, the Mean one explains the least lifespan inequality dynamics, suggesting that shifts in cause-specific mean ages at death alone contributed little to changes in lifespan inequality.

Gap in protective behaviors between Han and minority ethnicities during COVID-19 pandemic in rural western China: A decomposition analysis

Understanding the ethnic gap in protective behavior and its explanatory factors is a promising step for reducing pandemic-induced disparities. However, no studies have endeavored to identify the factors contributing to a gap in protective behaviors between Han and minority ethnicities during COVID-19 pandemic in rural China. We aimed to analyze the gap in protective behaviors between Han and minority residents in rural China. We conducted cross-sectional studies in multi-ethnic rural China in 2020. A total of 1640 participants from Han and minority groups were invited to participate. The decomposition method was applied to analyze the gap in protective behaviors and its associated factors between the Han and minority groups. Participants in the Han group had a higher protective behavioral score (9.26 ± 1.20) than the minority group (8.97 ± 1.50), yielding a significant gap in protective behaviors between Han and minority ethnicities of 0.29. Socio-demographic characteristics, health status, the degree of knowledge held about COVID-19, and psychological responses to COVID-19 explained 79.3 % (0.23/0.29) of the behavioral gap between the Han and minority groups. The difference in household asset levels was the largest explained contributor to the behavioral gap (52.17 %) (0.12/0.23), followed by fear felt for COVID-19 (-21.74 %) (-0.05/0.23). Differences in educational attainment, degree of knowledge held about COVID-19, and self-efficacy in response to COVID-19 each explained 17.4 % (0.04/0.23) of the behavioral gap. In conclusion, Han group show greater protective behaviors than minority ethnic groups. To drive better protective behavior in the most vulnerable communities, targeted, group-specific COVID-19 preventative messages deployed in public health communication strategies is suggested to enhance individual confidence in coping with the pandemic while creating a healthy amount of fear for public health crisis.

Income-related inequality in obesity and its determinants in Spain: What happens beyond the obesity threshold?

This paper computes and decomposes income-related inequalities in three metrics of obesity, namely, status, depth and severity, for Spain, a European country characterized by a universal health care system with very high and rising obesity prevalence rates. Furthermore, this paper investigates the main determinants of the reduction in obesity inequalities observed over time among the female Spanish population. To compute these inequality indexes, we use cross-sectional and individual-level data gathered from the Spanish National Health Survey. We document income-related inequalities in obesity, that are more pronounced in depth and severity and are to the detriment of poor women in Spain. University education is the most important determinant for all three inequality indexes. We further report that inequalities in obesity tend to decline over time for women, which is explained mainly by a substantial decrease in the degree of inequality in secondary education and a large decrease in the income elasticity of obesity.

from 2004 to 2018: A decomposition analysis

Average sleep duration in the United States declined in recent years, and the decline may be linked with many biopsychosocial factors. We examine how a set of biopsychosocial factors have differentially contributed to the temporal trends in self-reported sleep duration across racial groups between 2004-2005 and 2017-2018. Using repeated nationally representative cross-sections from the National Health Interview Survey, we decompose the influence of biopsychosocial factors on sleep duration trends into two components. One component corresponds to coefficient changes (i.e., changes in the associations between behaviors or exposures and sleep duration) of key biopsychosocial factors, and the other part accounts for the compositional changes (i.e., changes in the distributions of exposures) in these biopsychosocial factors during the study period. We reveal that changes in the coefficients of some biopsychosocial factors are more important than compositional changes in explaining the decline in sleep duration within each racial/ethnic group. Our findings highlight racial differences manifest across multiple biopsychosocial domains that are shifting in terms of association and composition. Methodologically, we note that the standard regression approach for analyzing temporal trends neglects the role of coefficient changes over time and is thus insufficient for fully capturing how biopsychosocial factors may have influenced the temporal patterns in sleep duration and related health outcomes.

Assessment of land use change and carbon emission: A Log Mean Divisa (LMDI) approach

Changes in land use have a notable influence on carbon emissions since they can affect the levels of carbon stored in both soil and vegetation. To effectively analyze the factors influencing carbon emissions from land use change, the Log Mean Divisa (LMDI) method is commonly employed. The LMDI method is a decomposition analysis that dissects changes in carbon emissions into different factors, including shifts in land use patterns, population growth, economic activity, and energy intensity. This approach enables the identification of specific drivers of carbon emission changes and the development of targeted policy interventions to address them. To explore the relationship between land use change, carbon emissions, and the LMDI method, a case study analysis can be conducted. This involves selecting a particular region or country experiencing land use change and examining the factors driving these transformations. Subsequently, the LMDI method can be applied to decompose the changes in carbon emissions within the selected region or country, thereby pinpointing the major contributors to these changes. In our study, we observed the necessity of regulating energy consumption and greenhouse gas emissions in urban communities through sustainable practices and technologies. The research highlighted variations in energy consumption, emissions, renewable energy utilization, and public transportation usage among selected cities in China. Moreover, the study demonstrated land use patterns and their associated carbon emissions, alongside the findings of the LMDI analysis, which explored carbon emissions based on different land use patterns. The study illuminates the importance of understanding the relationship between land use change and carbon emissions, employing the LMDI method as a valuable analytical tool. It underscores the significance of sustainable practices and technologies in mitigating carbon emissions in urban areas and provides insights into the role of land use patterns in shaping carbon emission outcomes.

Going green while getting lean: Decomposing carbon and green total factor productivity

While research on carbon productivity is growing rapidly, the role of structural change in green transition remains unexplored due to the scarcity of firm-level emission data. This study addresses this gap by utilizing unique register-based greenhouse gas emission data from Finland's energy-intensive manufacturing firms for 2000-2019. Applying a structural change productivity decomposition, we break down the sector's carbon productivity and green total factor productivity into four components: contributions from non-switching continuing firms, industry-switching continuing firms, the effects of entry and exit, and resource allocation. The findings highlight the important role of structural change in the sector's productivity. Non-switching continuing firms emerged as the key drivers of both carbon and green total factor productivity growth. The contribution of entry and exit was negative during the financial crisis, while inefficient resource allocation significantly hindered productivity growth throughout the study period. These findings emphasize the importance of public subsidies targeted at environmentally efficient firms to enhance their competitiveness under challenging market conditions. Furthermore, the establishment of a stable yet positive carbon price would incentivize less-productive firms to adopt environmentally friendly technologies.

The impact of COVID-19 on life expectancy across socioeconomic groups in Denmark

BACKGROUND

Denmark was one of the few countries that experienced an increase in life expectancy in 2020, and one of the few to see a decrease in 2021. Because COVID-19 mortality is associated with socioeconomic status (SES), we hypothesize that certain subgroups of the Danish population experienced changes in life expectancy in 2020 and 2021 that differed from the country overall. We aim to quantify life expectancy in Denmark in 2020 and 2021 by SES and compare this to recent trends in life expectancy (2014-2019).

METHODS

We used Danish registry data from 2014 to 2021 for all individuals aged 30+. We classified the study population into SES groups using income quartiles and calculated life expectancy at age 30 by year, sex, and SES, and the differences in life expectancy from 2019 to 2020 and 2020 to 2021. We compared these changes to the average 1-year changes from 2014 to 2019 with 95% confidence intervals. Lastly, we decomposed these changes by age and cause of death distinguishing seven causes, including COVID-19, and a residual category.

RESULTS

We observed a mortality gradient in life expectancy changes across SES groups in both pandemic years. Among women, those of higher SES experienced a larger increase in life expectancy in 2020 and a smaller decrease in 2021 compared to those of lower SES. Among men, those of higher SES experienced an increase in life expectancy in both 2020 and 2021, while those of lower SES experienced a decrease in 2021. The impact of COVID-19 mortality on changes in life expectancy in 2020 was counterbalanced by improvements in non-COVID-19 mortality, especially driven by cancer and cardiovascular mortality. However, in 2021, non-COVID-19 mortality contributed negatively even for causes as cardiovascular mortality that has generally a positive impact on life expectancy changes, resulting in declines for most SES groups.

CONCLUSIONS

COVID-19 mortality disproportionally affected those of lower SES and exacerbated existing social inequalities in Denmark. We conclude that in health emergencies, particular attention should be paid to those who are least socially advantaged to avoid widening the already existing mortality gap with those of higher SES. This research contributes to the discussion on social inequalities in mortality in high-income countries.

Greenhouse gas emissions trends and drivers insights from the domestic aviation in Thailand

Domestic aviation is a swiftly expanding contributor to global greenhouse gas (GHG) emissions. Presently, economic volatility and the Coronavirus disease (COVID-19) crisis have resulted in the decline of domestic aviation, but domestic aviation is rapidly recovering in many countries. However, from a GHG emissions viewpoint, the domestic aviation sector is largely unenforced even though the International Civil Aviation Organization's (ICAO) Carbon Offsetting and Reduction Scheme for International Aviation (CORSIA) provision for international aviation is currently in place. Accordingly, the knowledge base on emissions and their drivers from domestic aviation is weak, especially in developing countries, thus hindering an evidence-based policy debate. In this context, we have estimated and analyzed the pre-COVID-19 GHG emissions and their trends from commercial domestic aviation in Thailand; and provided insights on the role of key drivers that influence GHG emissions that are expected to be useful not only for Thailand but also for other developing countries. Emissions are estimated following Intergovernmental Panel on Climate Change (IPCC) Tier-II. Specifically, activity-based landing/take-off (LTO) cycle and cruise. This is compared to the Tier-I method, and key drivers were analyzed using an index decomposition method. The total annual average GHG emissions for all LTO cycles and cruises of commercial domestic aviation for 2015-2020 was 2254 Th. tonnes of CO2-eq. During the LTO cycle of the aircraft, GHG emissions were at an average of 983 Th. tonnes of CO2-eq. Additionally, during the cruise stage, emissions averaged 1270 Th. tonnes of CO2-eq. The choice of accounting methods (i.e., IPCC Tier II vs. Tier I) seems to have had only nominal implications. Our analysis showed that, in the 2008-2020 period, the aviation activity effect and economic growth were the key decisive factors in this sector's GHG emissions growth. It was followed by the fuel energy intensity levels and the population effect in descending order of impact. These findings have significant ramifications for present and future policies aimed at decreasing GHG emissions, aiding Thailand in achieving its climate targets by 2050, and enhancing energy efficiency as the domestic aviation market adapts.

Inpatient healthcare utilization among people with disabilities in Iran: determinants and inequality patterns

BACKGROUND

People with disabilities (PWD) have different health service needs and different factors affect the utilization of these services. Therefore, the aim of this present study was to identify determinants of inpatient healthcare utilization among PWDs in Iran.

METHODS

This research was a secondary data analysis of a cross-sectional study. The present study used data gathered for 766 PWDs (aged 18 years and older) within the Iranian Society with Disabilities (ISD) between September and December 2020. Multiple logistic regression models calculated adjusted odds ratios (aOR) and 95% confidence intervals in order to identify determinants of inpatient healthcare utilization among PWDs.

RESULTS

Data for 766 people with disabilities were analyzed. A large number of participants were over 28 years of age (70.94%), male (64.36%), and single (54.02%). In the present study, more than 71% of participants had no history of hospitalization during the last year. In this study, males [aOR 2.11(1.14-3.91), participants with Civil Servants health insurance coverage [aOR 3.44 (1.16 - 10.17)] and individuals in the 3th quartile of disability severity [aOR 2.13 (1.01 - 4.51)] had greater odds of inpatient healthcare utilization compared to the other groups. The value of the concentration index (C) for inpatient healthcare utilization was - 0.084 (P.value = 0.046). The decomposition analysis indicated that gender was the greatest contributor (21.92%) to the observed inequality in inpatient healthcare utilization among participants.

CONCLUSION

Our findings suggested that the likelihood of hospitalization among the study participants could be significantly influenced by factors such as gender, the health insurance scheme, and the degree of disability severity. These results underscore the imperative for enhanced access to outpatient services, affordable insurance coverage, and reduced healthcare expenditures for this vulnerable population. Addressing these issues has the potential to mitigate the burden of hospitalization and promote better health outcomes for disadvantaged individuals.

Factors Contributing to the Change in Overweight/Obesity Prevalence Among Indian Adults: A multivariate decomposition analysis of data from the National Family Health Surveys

INTRODUCTION

Concerns over the escalating burden of non-communicable diseases call for the redressal of behavioral risk factors like increased body mass index. Most studies have failed to quantify the contribution of socio-demographic characteristics in a linear trend. The present study aims to estimate the current prevalence of overweight and obesity in Indian adults and the contribution of different socio-demographic factors to the increasing prevalence.

METHODS

We carried out a secondary data analysis of two National Family Health Survey (NFHS) rounds. The final sample includes 558,122 women and 84,477 men from round 4, and 574,099 women and 74,761 men were included from round 5, using a multi-stage stratified random sampling approach. Overweight/obesity was our primary dependent variable. Weighted bivariate analysis was used to ascertain the prevalence, and the adjusted odds ratios were computed to ascertain the potential predictors. The contribution of different factors towards rising burden over two time points was estimated using multivariate decomposition analysis for non-linear response models.

RESULTS

Overall weighted prevalence of overweight and obesity in males and females per NFHS-5 was 44.02% and 41.16%, respectively, compared to 37.71% and 36.14% in NFHS-4. Decomposition analyses depict that the proportion of obesity increased by 6.37% and 5.10% points among men and women, respectively, over the two rounds. Compositional differences of participants (endowment) attributed to 16.54 and 49.90% differences, and the difference in coefficient or effect accounted for 83.46 and 50.10%, respectively, of the increase in the prevalence. The most significant factors contributing to increased prevalence were age, improving socio-economic status, smoking, unclean cooking fuel, and diabetes.

CONCLUSIONS

The incremental rise in such a short period, mainly attributed to the effect of socio-demographic variables, is concerning. Policy interventions should prioritize health advocacy programs and aggressively target behavioral modifications while preparing the health systems to manage the people living with obesity.

Global, regional, and national burden of liver cancer due to non-alcoholic steatohepatitis, 1990-2019: a decomposition and age-period-cohort analysis

BACKGROUND

Identifying past temporal trends in non-alcoholic steatohepatitis (NASH)-associated liver cancer (NALC) can increase public awareness of the disease and facilitate future policy development.

METHODS

Annual deaths and age-standardized death rates (ASDR) for NALC from 1990 to 2019 were collected from the Global Burden of Disease (GBD) 2019 study. The long-term trend and the critical inflection of mortality of NALC were detected by Joinpoint analysis. Age-period-cohort analysis was employed to evaluate the effects of age, period, and cohort. Last, decomposition analysis was used to reveal the aging and population growth effects for NALC burden.

RESULTS

Between 1990 and 2019, the ASDR of NALC witnessed an overall declining trend on a global scale, with a decrease in females and a stable trend in males. However, the global ASDR demonstrated a significant upward trend from 2010 to 2019. Southern sub-Saharan Africa and Southeast Asia have the highest NALC burdens, while high socio-demographic index (SDI) region experienced the fastest escalation of NALC burdens over 30 years. The decomposition analysis revealed that population growth and aging were the primary catalysts behind the increase in global NALC deaths. Age-period-cohort analyses showed that NALC mortality declined the fastest among females aged 40-45 years in high SDI region, accompanied by a deteriorating period effect trend during the period of 2010-2019.

CONCLUSION

The global absolute deaths and ASDR of NALC have witnessed a rise in the past decade, with populations exhibiting considerable disparities based on sex, age, and region. Population growth, aging, and metabolism-related factors were the main factors behind the increase in global NALC deaths.

Urban-rural and gender differential in depressive symptoms among elderly in India

Background

To date, evidence remained inconclusive explaining rural-urban and male-female differential in depression. Unlike other previous research on the association of several risk factors with depressive symptoms among the elderly, this study focussed on the socio-economic status-related inequality in the prevalence of depression among the elderly along with focussing urban-rural and male-female gradients of depression among the elderly.

Methods

This study used data from Longitudinal Ageing Study in India (LASI) Wave-I, 2017-18, survey. The outcome variable for this study was self-reported depression. Bivariate analysis was used to understand the prevalence by sociodemographic clusters. Fairlie decomposition analysis has been done to measures rural-urban inequalities for depression among older men and women.

Results

Results found that around 22 percent of urban elderly and 17 percent of rural elderly reported depression. A higher proportion of female elderly (22.6% vs. 18.4%) reported depression than male elderly. Almost one in every five elderly (20.6%) reported depression in India. The results found that a higher percentage of women in rural and urban areas reported depression than their male counterparts. While examining SES-related inequality in the prevalence of depression, education was a significant factor explaining the SES-related inequality in the prevalence of depression among female elderly and not in male elderly.

Conclusion

Given the large proportion of elderly reporting depression, this study highlights the need for improving health care services among the elderly. The increasing burden of depression in specific sub-populations also highlights the importance of understanding the broader consequences of depression among rural and female elderly.

Socioeconomic inequality in teenage pregnancy in Papua New Guinea: a decomposition analysis

BACKGROUND

Teenage pregnancy is a global public health issue, and it poses a serious threat to the health and socioeconomic status of mothers and their newborn children. Although Papua New Guinea has recorded one of the highest teenage pregnancy rates among Asia-Pacific countries, few studies have conducted research on the related inequality in the country. Therefore, this study aimed to assess socioeconomic inequality in teenage pregnancy and its contributing factors in Papua New Guinea.

METHODS

Data for this cross-sectional study were obtained from the 2016-2018 Papua New Guinea Demographic and Health Survey. The analytical sample consisted of 2,864 girls aged 15-19 years. We employed Erreygers normalized concentration index (ECI) and concentration curves to measure and depict socioeconomic inequality in teenage pregnancy. Decomposition analysis was likewise performed to identify the contributions of determinants to the observed inequality.

RESULTS

Weighted ECI for teenage pregnancy was - 0.0582 (P < 0.001), thereby indicating that teenage pregnancy in Papua New Guinea is disproportionately concentrated among poor girls. Decomposition analysis suggested that education level (65.2%), wealth index (55.2%), early sexual debut (25.1%), region (8.5%), and sex of household head (4.1%) are the main determinants explaining the pro-poor socioeconomic inequality in teenage pregnancy.

CONCLUSIONS

A pro-poor socioeconomic inequality of teenage pregnancy was present in Papua New Guinea. This inequality may be alleviated by such interventions as ensuring that teenage girls receive education; implementing poverty alleviation projects, eliminating child, early, and forced marriages; strengthening promotion for household head to support teenagers in accessing sexual and reproductive health education; improving geographical accessibility to health facilities on contraceptive services, and taking necessary precautions and responses to sexual misconduct.

Prolonged war reverses carbon emissions from an early decline to a late increase - Evidence from Syria

Given that war can have a serious impact on the climate, this article is aimed to discuss the impact of warfare on carbon emissions by examining changes in CO2 before and during the war in Syria based on the kaya constant equation and the LMDI decomposition method. In the decade before the war, population was the largest contributor, making up 32.64% of the total 51.02% increase in carbon emissions. The only factor that offsetting carbon emissions was energy intensity, making a 22.30% curbing effect. In the early stage of the war, carbon emissions decreased by 56.38%, in which per capita GDP contributed 37.55% of the total CO2 decline. Carbon intensive of energy was the only factor promoting the carbon increase with a 4.67% contribution. In the late war, carbon emissions start to resume slow increase with energy intensity and economy turning negative to positive. It can be speculated that the impact of the war on CO2 emissions: (i) in the first years of the war, CO2 would drop significantly at the cost of significant population decline and economic recession, the least desirable and the worst way to reduce carbon emissions. (ii) if evolves into a prolonged war, it would reverse carbon emissions from decline to increase, although the population and the economy are both falling. This research, therefore contends that once war is triggered, there is no other solution to prevent this worst-case scenario of Population Decline - Economic Recession - Increased Carbon Emissions from happening, unless the war is stopped immediately.

Emission accounting and drivers in Central Asian countries

Emerging countries are at the frontier of climate change actions, and carbon emissions accounting provides a quantifiable measure of the environmental impact of economic activities, which allows for comparisons of emissions across different entities. However, currently there is no study covering detailed emissions inventories for emerging countries in Central Asian. This paper compiles detailed and accurate carbon emissions inventories in several Central Asian countries (i.e., Kazakhstan, Kyrgyzstan, Pakistan, Palestine, Tajikistan, and Uzbekistan) during the period 2010-2020. Using the IPCC administrative territorial approach, we for the first time compile their emissions inventories in 47 economic sectors and five energy categories. Moreover, we also investigate decoupling status based on Tapio decoupling model and examine emissions driving factors based on the index decomposition analysis method. The primary results illustrate that carbon emissions in Central Asian countries are increasing with huge differences. Decoupling results highlight that most of the sample countries still need more effort to decouple the economy and emissions except that Pakistan achieves an ideal strong decoupling state. The results of the decomposition indicate that the economy and population both raise emissions, while energy intensity and carbon intensity are negative drivers in some countries. We propose practical policy implications for decarbonization and energy transition roadmap in Central Asian countries.

Analysis of energy-related CO2 emissions in Pakistan: carbon source and carbon damage decomposition analysis

Carbon dioxide emissions (CO2es) are presently a hot topic of worldwide concern. It is of great significance for lessening CO2es to wholly understand the transformation pattern of CO2es among countries, industries, and the main factors (i.e., emission effect, energy intensity, economic development, population size, carbon per unit of land, land per capita, and environmental impact per capita effects) influencing CO2es. Thus, to mitigate the country's CO2es efficiently, it is necessary to determine the driving factors of its emissions and damage variations. For this, we use the logarithmic mean Divisia index method. This research decomposes the major two dimensions, such as carbon sources and carbon damage variations from 1986 to 2020, into eight factors. The results show that Pakistan's CO2es increased continuously during the period, with an average annual growth rate of 4.76%. Growing the country's CO2es over 1986-2020, the key influencing factors are economic development, population, and land, while energy intensity and emission factors are the main forces in mitigating CO2es. The carbon source and carbon damage dimensions reached 68.75 Mt and 208.56 Mt, respectively, which led to a rise in CO2e. The entire set of factors is averagely moving around the major outcomes that provide significant policy measures. Finally, to efficiently reduce CO2e, Pakistan should concentrate on specific industrial paths and implement challenging, comprehensive governance to attain a low-carbon chain throughout the process. Thus, based on empirical results, this research put forward policy suggestions for cleaner production to reduce CO2 emissions further, and environmental policies must be tailored to local conditions.

Mortality and years of life lost due to pancreatic cancer in China, its provinces, urban and rural areas from 2005 to 2020: results from the national mortality surveillance system

BACKGROUND

Pancreatic cancer is a growing public health concern in China, and depicting it from different perspectives would provide a comprehensive understanding of its epidemiological characteristics.

METHODS

Data from the National Mortality Surveillance System (NMSS) in China was used to estimate the number of deaths, years of life lost (YLL), age-standardized mortality rate (ASMR) and age-standardized YLL rate in China, its provinces and urban-rural areas from 2005 to 2020. Joinpoint regression analysis was employed to explore the temporal trends of ASMR and age-standardized YLL rate. Decomposition analysis was conducted to assess the contribution of population growth, population aging and cause-specific mortality rate to the increment of pancreatic cancer deaths.

RESULTS

A total of 100,427 pancreatic cancer deaths and 2,166,355 pancreatic cancer related YLL were estimated in China in 2020. The overall ASMR significantly increased from 6.6/100 000 in 2005 to 7.4/100 000 in 2020, and was higher in men than that in women. Age-standardized YLL rate showed a similar trend. The mortality rates of pancreatic cancer were generally higher in northeast China than in southwest China. The highest ASMRs were found in Jilin, Zhejiang, Inner Mongolia and Anhui, and the lowest ones in Guangxi, Yunnan, Tibet, and Hainan. The disease burden due to pancreatic cancer presented a significant upward trend in rural areas and a downward trend in urban areas.

CONCLUSIONS

The burden associated with pancreatic cancer had been increasing in China from 2005 to 2020. The escalating disease burden of pancreatic cancer in rural areas necessitates the implementation of effective control and prevention measures. Relevant provinces should pay greater attention to the prevailing of pancreatic cancer, particularly those exhibiting higher mortality rates.

Spatial evolution and decomposition of energy-related CO2 emissions in China's mining industry: from the perspective of regional heterogeneity

To ensure China's energy security, the mining industry faces increasing emissions reduction and energy conservation pressures. This study combined index and production-theoretical decomposition analyses to decompose the energy-related CO2 emissions in mining industry (ERCEMI) influencing factors into seven major effects and adopted a gravity model to dynamically visualize the transfer path and gravity distribution from 2000 to 2015. As investment effects were introduced into the decomposition analysis, the results fully considered the regional heterogeneity and spatiotemporal dynamics. The main findings were as follows: (i) a typical heavy emissions trend along the Heihe-Tengchong line, with a concentration of large ERCEMI values; (ii) the gravity center of ERCEMI had shifted to the southwest, and the migration trends were divided into three stages; (iii) the ERCEMI had strong regional heterogeneity, with a diffusion trend from north to south and shrinking from east to west; (iv) the potential energy intensity and investment efficiency effects had significantly inhibited the ERCEMI, while the investment scale had boosted it. Implications for regional layouts, energy intensity reductions, and investment optimization are discussed. This research provides a comprehensive regional analysis for ERCEMI reductions and the sustainable development of the mining industry and provides a reference for local industrial development planning.

Changes in contributions of age- and cause-specific mortality to the widening life expectancy gap between North and South Korea, 1990-2019: An analysis of the Global Burden of Disease Study 2019

Background

Life expectancy gaps between North and South Korea have increased but contributions to these gaps remain poorly understood. Using data from the Global Burden of Disease Study (GBD) 2019, we examined how much death from specific diseases contributed to these gaps in different age groups over three decades.

Methods

Data for death numbers and population by sex and 5-year age groups in both North and South Korea from 1990 to 2019 were extracted from the GBD 2019 to calculate life expectancy. Joinpoint regression analysis was conducted to investigate changes in life expectancy in North and South Korea. We used decomposition analysis to partition differences in life expectancy within and between the two Koreas into changes in age- and cause-specific death contributions.

Results

Life expectancy increased in two Koreas from 1990 to 2019, but North Korea experienced a marked decline in life expectancy during the mid-1990s. The life expectancy gaps between the two Koreas were greatest in 1999, with a difference of 13.3 years for males and 14.9 years for females. The main contributors to these gaps were higher under-5 mortality from nutritional deficiencies for males (4.62 years) and females (4.57 years) in North Korea, accounting for about 30% of the total gap in life expectancy. After 1999, the life expectancy gaps reduced but persisted with differences of about ten years by 2019. Notably, chronic diseases contributed to about 8 out of 10 years of life expectancy gap between the two Koreas in 2019. Differential cardiovascular disease mortality in the older groups was the main contributor to the life expectancy gap.

Conclusions

The contributors to this gap have shifted from nutritional deficiencies in children younger than five years to cardiovascular disease among elderly people. Efforts for strengthening social and healthcare systems are needed to curb this large gap.

Spatiotemporal patterns and drivers of carbon emissions from municipal solid waste treatment in China

Reducing carbon emissions from municipal solid waste (MSW) treatment is non-negligible for China to meet its "carbon peaking and carbon neutrality" targets. It is critical to objectively evaluate the spatiotemporal patterns and drivers of carbon emissions from MSW treatment. This study estimates the carbon emissions from MSW treatment across 30 Chinese provinces from 2011 to 2020. The joint approach LMDI-PDA model is further used to refine the impact of policy on carbon emission changes from technical and efficiency perspectives, while considering the socio-economic factors. The results showed that carbon emissions from MSW treatment grew significantly until peaking at 202.05Mt CO2e in 2017 and then stabilized, finally dropping to 165.10 Mt CO2e in 2020 due to the impact of COVID-19. Compared with the "12th Five-Year Plan" period, the MSW emissions intensity declined significantly during the "13th Five-Year Plan" period, indicating the effective implementation of waste emission control measures. Furthermore, the slowdown in the growth of national emissions was primarily driven by technological advances in waste treatment. Technical efficiency change effect, MSW generation intensity effect, economic scale effect, and population scale effect impeded national emissions decline. Since the performance of various drivers varied greatly in different provinces, a cluster analysis was conducted to provide policy recommendations in provinces with similar characteristics. Both the methods and results of this study can provide better decision-making support for national and provincial carbon emissions control policies targeting MSW treatment.

Incident risk and burden of cardiovascular diseases attributable to long-term NO2 exposure in Chinese adults

BACKGROUND

A number of studies suggested a nexus between long-term exposure to nitrogen dioxide (NO2) and the incidence of cardiovascular disease (CVD), while population-based cohort evidence in low- and middle-income countries was extensively sparse.

METHODS

We carried out an 8-year longitudinal study (2010-2018) in a nationwide dynamic cohort of 36,948 Chinese adult participants, who were free of CVD at baseline. Annual average estimates of NO2 exposure were predicted using a well-validated spatiotemporal model and assigned to study participants based on their residential counties. Considering death as a competing risk event, Fine-Gray competing risk models with time-varying exposures at an annual scale were used to quantify incident risks of overall CVD, hypertension, and stroke associated with a 10-μg/m3 rise in NO2 exposure. Using the meta-analysis approach, we performed a pooled analysis of hazard ratio (HR) drawn from this and prior multinational cohort studies for the assessment of attributable burden. NO2-attributable overall CVD incidents in China were evaluated by city and province for years 2010 and 2018, referring to a counterfactual exposure level of 10 μg/m3 (2021 World Health Organization [WHO] air quality guidelines). A decomposition method was used to decompose net change in NO2-attributable CVD incidents during 2010 and 2018 into 3 primary contributions of driving factors (i.e., changes in NO2 exposure, population size, and incidence rate).

RESULTS

A total of 4428 overall CVD events (hypertension 2448, stroke 1044) occurred during a median follow-up period of 6.1 years. Annual mean NO2 concentration from 2010 to 2018 was 20.0 μg/m3 (range: 6.9-57.4 μg/m3). An increase of 10-µg/m3 in NO2 was associated with an HR of 1.558 (95% confidence interval [CI]: 1.477, 1.642) for overall CVD, 1.521 (95% CI: 1.419, 1.631) for hypertension, and 1.664 (95% CI: 1.485, 1.865) for stroke. Longitudinal associations of NO2 exposure with incident CVD were nearly linear over the exposure range, suggesting no discernible thresholds. Subgroup analyses indicated significantly higher NO2-associated risks of incident CVD among urban residents and overweight/obese individuals. According to pooled HR of NO2-CVD association (1.108, 95% CI: [1.007, 1.219]) from 10 multinational cohort studies, we estimated totally 1.44 million incident CVD cases attributable to NO2 exposure in 2018, representing a substantial decrease of 0.41 million compared to the estimate in 2010 (1.85 million) in mainland of China. Nationally, from 2010 to 2018, the attributable incident cases greatly dropped by 22.4%, which was dominantly driven by declined NO2 concentration (-47.1%) that had offset far from the rise of CVD incidence rate (+19.6%) and population growth (+5.1%).

CONCLUSIONS

This study provided nationwide cohort evidence for elevated risks of CVD incidence associated with long-term ambient NO2 exposure among Chinese adults, particularly in urban areas and among overweight/obese individuals. Our findings highlighted that reducing NO2 exposure below 2021 WHO guideline could help prevent a substantial portion of incident CVD cases in China.

Socioeconomic inequality in early sexual initiation among female youths in sub-Saharan African countries: a decomposition analysis

INTRODUCTION

Youths are defined as individuals within the age group 15-24 years. It is the transitional stage from childhood to adulthood with biological, social, and psychological change, so it is a time of risk and opportunity for their future life. Early sexual initiation exposes young people to various social, economic, sexual, and reproductive health issues, such as unwanted adolescent pregnancies, sexually transmitted infections, unsafe abortion, cervical cancer, and early marriages. Therefore, this study aimed to assess the presence of socioeconomic inequality in early sexual initiation and contributing factors in sub-Saharan African countries.

METHODS

A total of 118,932 weighted female youths from SSA countries' DHS data were included in the study. Socioeconomic inequality of Early sexual initiation was evaluated using the Erreygers znormalized concentration index and associated concentration curve. Decomposition analysis was performed to determine those factors causing socioeconomic-related inequality.

RESULTS

The weighted Erreygers normalized concentration index of wealth-related inequality of early sexual initiation was - 0.157 with a Standard error = 0.0046 (P value < 0.0001); this indicated that early sexual initiation was disproportionately concentrated among the poor (pro-poor). Moreover, the weighted Erreygers normalized concentration index (ECI) of educational status-related inequality of early sexual initiation was - 0.205 with a Standard error = 0.0043 (P value < 0.0001). This indicated that early sexual initiation was disproportionately concentrated among youths with no formal education. The decomposition analysis revealed that mass media exposure, wealth index, place of residency, religion, marital status, educational status, and age were significant contributors to the pro-poor socioeconomic inequalities in early sexual initiation.

CONCLUSION AND RECOMMENDATION

This study has revealed pro-poor inequality in early sexual initiation. Therefore, priority must be given to modifiable factors such as promoting the accessibility of media exposure in the household, improving the educational opportunity of female youths, and improving their country's economy to a higher economic level to improve the wealth status of the population.

Changes in agricultural land use and its consequences on crop productivity, diversity, and food availability in an agriculturally developed state of India

The present study, covering a period of 52 years (1966-2017), explores changes in agricultural land use and its consequences on crop productivity, diversity, and food availability in Haryana, an agriculturally developed state of India. The time series data on different parameters (area, production, yield, etc.) were collected from the secondary sources and analyzed with the help of compound annual growth rate, trend tests (simple linear regression and Mann-Kendall), and change point detection tests such as Pettitt, standard normal homogeneity, Buishand range, and Neumann ratio. Apart from above, the relative share of area and yield to total change in output was determined using decomposition analysis. The results revealed that agricultural land use became intensive and underwent significant alteration with multifold shifting in area from coarse cereals (maize, jowar, and bajra) to fine food grains (wheat and rice). The yield of all crops, especially wheat and rice witnessed a significant increase which subsequently led to an upsurge in their production. However, the production of maize, jowar, and pulses recorded negative growth despite of an increase in their yield. The results also revealed manifold increase in use of modern key inputs during the first two periods (1966-1985), but afterwards input use rate slowed down. Additionally, the decomposition analysis revealed that yield effect remained positive in changing the production of all crops, but area contributed positively only in wheat, rice, cotton, and oilseeds. The major findings of this study imply that the production of crops can be enhanced only through improvement in yield because there is no further scope left for horizontal expansion in cultivable area of the state.

Key drivers of the textile and clothing industry decarbonisation within the EU-27

The European Union has identified the Textile and Clothing industry as one of the essential objectives towards carbon neutrality in 2050 in line with the "European Green Deal". There are no previous research papers focused on analysing the drivers and inhibitors of the past greenhouse gas emission changes of the textile and clothing industry in Europe. This paper aims to analyse the determinants of the changes in these emissions, and the disassociation level between emissions and economic growth, throughout the 27 Member States of the European Union, from 2008 to 2018. A Logarithmic Mean Divisia Index that explains the key drivers of the changes in greenhouse gas emissions of European Union Textile and Cloth industry and a Decoupling Index have been applied. The results generally conclude that the intensity and carbonisation effects are key factors that contribute to reducing greenhouse gas emissions. The lower relative weight of the textile and clothing industry throughout the EU-27 was noteworthy, and favours lower emissions, partially counteracted by the activity effect. Also, most Member States have been decoupling the industry's emissions from economic growth. Our policy recommendation shows that if further reductions in greenhouse gas emissions are to be achieved, energy efficiency improvements and cleaner use of energy sources would offset the potential increase in emissions of this industry as a result of a relative increase in its gross value added.

Refined assessment and decomposition analysis of carbon emissions in high-energy intensive industrial sectors in China

Carbon emissions from high-energy intensive industrial sectors are the focus of this study due to the huge energy consumption of these sectors. A refined carbon emission inventory of Chinese high-energy intensive industrial sectors in 2020 was first developed at the point source level. The results showed that coal-fired power plants (CFPPs) were the leading contributors to carbon emissions, followed by iron and steel smelting (ISS) and cement production (CMP). Provinces with high carbon emission intensity were mainly concentrated in the north and northeast coasts, while exhibiting a developed economic level and a concentration of heavy industries. Additionally, the growth in China's industrial carbon emissions from 1995 to 2020 can be divided into three phases. The largest decrease in emission intensity was observed in Central, Southwest, North, and East China. Furthermore, the economic structure remained the dominant driver of carbon emissions from the 10th to 13th Five-Year Plan (FYP), playing a positive promotional role. The contribution of economic structure, energy intensity, and energy structure to carbon emissions varied substantially by region and period. With the proposal of sustainable development and energy conservation in China, the influence of economic structure on the carbon emissions of industrial sectors has gradually weakened since the 11th FYP. The reduction in industrial carbon emissions in China under three scenarios could reach up to 46.6 % from 2030 to 2050. The results indicate that industrial carbon emission control in China needs to be integrated into the refined control pathway for conventional air pollutants, considering the spatial variability of industrial carbon emissions in China.

Rural-urban disparities in the unmet need for home visiting services among oldest-old in China: Changes over time and decomposition analysis

PURPOSE

This study aims to assess trends in rural-urban disparities in the prevalence of unmet community-based home visiting services need and their contributing factors from 2005 to 2018 among oldest-old in China.

METHODS

The Chinese Longitudinal Healthy Longevity Survey data of oldest-old collected with a targeted random-sampling approach from half of counties/cities from 23 provinces across China was used. Unmet need was measured as the differences between healthcare services expected and available. We used Cochran-Armitage tests to test linear trends in prevalence of unmet need. Average marginal differences were estimated to measure magnitude of rural-urban disparities in prevalence of unmet need. Changes in rural-urban disparities were decomposed using Blinder-Oaxaca Decomposition technique to logit models. All analysis was performed by Stata 15.0.

RESULTS

From 2005-2018, decreased trends in prevalence of unmet need were observed (overall: 62.4% to 48.6%; rural: 65.9% to 47.3%; urban: 57.5% to 49.8%) (all p_trend < 0.001). In 2017/2018, urban oldest-old reported greater prevalence of unmet need (average marginal difference, 95% CI: 3.7% [0.4%-7.1%]); affluent oldest-old reported less unmet need than their peers. Oldest-old from Central and Western China reported greater prevalence of unmet need than their Eastern peers. Increases in income (percentages of explained change, overall: 21.3%; rural: 16.9%, urban: 36.9%) mainly contributed to decreased trends in prevalence of unmet need.

CONCLUSIONS

Oldest-old with socioeconomic disadvantages or living in Central and Western China reported greater prevalence of unmet need. Policy efforts are warranted to ensure equitable access to home visiting services among those oldest-old.

Parental and Social Factors' Contribution to Adverse Pregnancy Outcomes with Urban-Rural Disparities - Four Provinces, China, 2011-2020

What is already known about this topic?

The prevalence of adverse pregnancy outcomes (APOs) exhibits a disparity between urban and rural areas, which is commonly associated with various factors, such as demographic and socio-environmental factors. However, the specific contribution of each factor has not yet been elucidated.

What is added by this report?

This study demonstrates that the primary factors contributing to urban-rural differences in the prevalence of APOs are population structure, parental age, parity, and regional development.

What are the implications for public health practice?

Future prevention and control measures should be directed toward considering population structure and regional differences. Accurate interventions will enhance the efficiency of public health services.

A temporospatial assessment of environmental quality in urbanizing Ethiopia

Global environmental quality has been negatively affected by urbanization, particularly vulnerable in the Sub-Saharan Africa. Therefore, understanding the underlying mechanism and driving forces for the change of environmental quality with urbanization process is essential to improve the environmental sustainability. In this study, the compounded night light index (CNLI) and remote sensing ecological index (RSEI) were used respectively to evaluate the urbanization level and environmental quality in Ethiopia from 2010 to 2020. On this basis, a temporospatial assessment framework was proposed, followed by methods of coupling coordination degree, spatial autocorrelation, elasticity, and decomposition. The results showed that 63 out of 690 woredas experienced environmental deterioration. Socioeconomic effect, carbon intensity, and climate change were decomposed as drivers to environmental quality, with socioeconomic effects contributing >68% of environmental improvement, while carbon intensity and climate change were responsible for >51% and >58% of environmental deterioration from 2010 values. Continuous increase in impervious surfaces resulted in a six-fold increase in surface runoff, which raised the flooding risk in sub areas and rural landscapes. This demands reforms of climate strategies and proper livestock management.

Emission growth and drivers in Mainland Southeast Asian countries

Mainland Southeast Asian (MSEA) countries (Cambodia, Laos, Thailand, Myanmar, and Vietnam) are likely to become one of the next hotspots for emission reduction, since CO₂ emissions in this area will have a two-thirds increase by 2040 due to rapid economy growth and associated energy consumption. As one of the most vulnerable areas to climate change, MSEA countries need to develop low-carbon roadmaps based on accurate emission data. This study provides emission inventories for MSEA countries for 2010-2019, based on the IPCC territorial emission accounting approach , including emissions from five types of fuels (i.e., coal, crude oil, oil products, natural gas, and biofuels & waste) used in 47 economic sectors. The results show that the emissions in MSEA countries are on the rise, with average annual growth rates ranging from 2.5% in Thailand to 19.3% in Laos. Biomass is one of the most important sources of carbon emissions, contributing between 11.8% and 76.7% of total carbon emissions, but its share has been declining in most countries, whereas the share of emissions from coal has risen sharply in Laos, Vietnam, and Cambodia. We further examine the drivers behind the changes in emissions using index decomposition analysis. Economic growth was the strongest driver of growth in emissions, while population growth has only had a small effect on emission growth. Energy intensity varies widely across nations, but only significantly reduced CO₂ emission growth in Thailand. The secondary sector considerable contributed to an increase in CO₂ emissions in Laos and Vietnam, while the tertiary sector only moderately contributed to emissions in Thailand. Our study provides a better understanding of the composition and underlying factors of emission growth in MSEA countries, this could shape their low-carbon development pathway. Our results could also inform other emerging economies, which may become emission hotspots in the next decades, to develop low-carbon roadmaps, thereby contributing to the achievement of global climate change targets.

Socioeconomic inequality in modern contraceptive utilization among reproductive-age women in sub-Saharan African countries: a decomposition analysis

INTRODUCTION

Family planning services allow individuals to achieve desired birth spacing, family size, and contribute to improved health outcomes for infants, children, women, and families, and prevent unintended pregnancy. Births resulting from unintended pregnancies can have negative consequences Children from unintended pregnancies are more likely to experience poor mental and physical health during childhood. Even though many international organizations work to ensure universal access to sexual and reproductive health services, reproductive health service utilization is concentrated among individuals with rich socioeconomic status. Therefore, this study aimed to assess the presence of socioeconomic inequality in modern contraceptive utilization and its contributors in sub-Saharan African countries.

METHODS

A total of 466,282 weighted reproductive-aged women samples from DHS data SSA countries were included in the study. Erreygers normalized concentration index and its concentration curve were used to assess socioeconomic-related inequality in modern contraceptive utilization. Decomposition analysis was performed to identify factors contributing to socioeconomic-related inequality.

RESULTS

The weighted Erreygers normalized concentration index for modern contraceptive utilization was 0.079 with Standard error = 0.0013 (P value< 0.0001); indicating that There is small amount but statistically significant pro rich distribution of wealth related in equalities of modern contraceptive utilization among reproductive age women. The decomposition analysis revealed that mass media exposure, wealth index., place of residency, and distance of health facility were the major contributors to the pro-rich socioeconomic inequalities in modern contraceptive utilization.

CONCLUSION AND RECOMMENDATION

In this study, there is a small amount but statistically significant pro rich distribution of modern contraceptive utilization. Therefore, give priority to modifiable factors such as promoting the accessibility of health facilities, media exposure of the household, and improving their country's economy to a higher economic level to improve the wealth status of the population.

Decomposition and comparative analysis of differences in depressive symptoms between urban and rural older adults: Evidence from a national survey

OBJECTIVES

The aim of this study was to investigate the factors influencing urban-rural differences in depressive symptoms among old people in China and to measure the contribution of relevant influencing factors.

DESIGN

A cross-sectional research. The 2018 data from The Chinese Longitudinal Health Longevity Survey (CLHLS).

SETTING

Twenty-three provinces in China.

PARTICIPANTS

From the 8th CLHLS, 11,245 elderly participants were selected who met the requirements of the study.

MEASUREMENTS

We established binary logistic regression models to explore the main influencing factors of their depressive symptoms and used Fairlie models to analyze the influencing factors of the differences in depressive symptoms between the urban and rural elderly and their contribution.

RESULTS

The percentage of depressive symptoms among Chinese older adults was 11.72%, and the results showed that rural older adults (12.41%) had higher rates of depressive symptoms than urban (10.13%). The Fairlie decomposition analysis revealed that 73.96% of the difference in depressive symptoms could be explained, which was primarily associated with differences in annual income (31.51%), education level (28.05%), sleep time ( - 25.67%), self-reported health (24.18%), instrumental activities of daily living dysfunction (20.73%), exercise (17.72%), living status ( - 8.31%), age ( - 3.84%), activities of daily living dysfunction ( - 3.29%), and social activity (2.44%).

CONCLUSIONS

The prevalence of depressive symptoms was higher in rural than in urban older adults, which was primarily associated with differences in socioeconomic status, personal lifestyle, and health status factors between the urban and rural residents. If these factors were addressed, we could make targeted and precise intervention strategies to improve the mental health of high-risk elderly.

What are the determinants of wastewater discharge reduction in China? Decomposition analysis by LMDI

Wastewater discharge reduction (WDR) is a key breakthrough point for China's environmental protection. Based on China's 30 provincial data from 2011 to 2017, this paper applied the logarithmic mean Divisia index (LMDI) method to clarify the determinants of WDR at national, regional, and provincial levels. Except for wastewater discharge factor, economic development, and total population, four innovative factors, total water application intensity, water environment cost, water treatment industry development level, and drainage infrastructure investment scale were first proposed in this study. The results indicated that from 2011 to 2017, at the national level, total water application intensity and water treatment industry development level were dominant contributors to WDR, while other factors all inhibited WDR. At the regional level, the results of wastewater discharge factor, economic development, and water environment cost were similar to the national level. The drainage infrastructure investment scale had a positive effect on WDR in Northeast and South China while having a negative effect on other regions. And except for Northeast China, the water treatment industry development level promoted WRD, while the total population inhibited WDR. Finally, the determinants of WDR at the provincial level were investigated. On this basis, targeted corresponding policies were provided in this paper.

Leverage of resource efficiency over environmental emissions: Case of a megacity in China

Material metabolism in a Chinese megacity, Shanghai, was investigated with an integrated approach. Production-based raw material input, city-wide waste output and carbon emissions were compiled for the period 1995-2020, by computing hundreds of products and by-products. Decoupling of these resource and environmental flows from economic development was assessed, and the socio-economic and technical drivers were decomposed. The research demonstrated a hypothesis that flows of primary resources, waste, and carbon emissions displayed a certain level of synchronicity in the past decades. An order effect was seen with waste indicators usually performing better than carbon indicators, and carbon indicators are better than resource indicators in terms of material/environmental intensity and decoupling. There might be a resource leverage leading to the synchronicity of environmental emissions. Improvement in resource efficiency was decomposed as the most significant driver to urban metabolism, bringing about >33 % of resource reduction, 32 % of carbon mitigation, and 30 % of waste diminution from the 2010 values. A greater extent in emission reduction than resource use was attributed to the decrease of fossil fuels share in total resource use and carbon intensity per energy consumption. Continuous increase in post-use waste flows caused a rebound of waste indicators in the recent five-year period (2016-2020) and broke up the synchronicity. This potentially foresees the shift of material metabolism from production to consumption side in major cities in China and calls for reforms of environmental policies.

The role of consumer choice in out-of-pocket spending on health

BACKGROUND

Analyses of out-of-pocket healthcare spending often suffer from an inability to distinguish necessary from optional spending in the data without making further assumptions. We propose a two-dimensional rating of the spending categories often available in household budget survey data where we consider the requirement to pay for necessary healthcare as one dimension and the incentive to pay extra for additional services, higher quality options or more convenience as a second dimension to assess the distortionary potential of higher spending for additional healthcare or higher quality options.

METHODS

We use three waves of a large German Household Budget Survey and decompose the Kakwani-index of total out-of-pocket healthcare spending into contributions of the eleven spending categories available in our data, across which user charge regulations vary considerably. We compute and decompose Kakwani-indexes for the different spending categories to compare the degrees of regressiveness across them.

RESULTS

The results suggest that categories with higher incentives for additional spending exhibit smaller contributions to the overall regressive effect of total out-of-pocket spending than categories where spending is presumably mostly on necessary and effective care.

CONCLUSIONS

Assessing the consumer choice potential of different spending categories is important because extra spending among the better-off may outweigh necessary spending in aggregate expenditure data, and may also hint at potential inequalities in the quality of provided healthcare.

Socioeconomic inequality in cognitive impairment among India's older adults and its determinants: a decomposition analysis

BACKGROUND

Cognitive impairment (CoI) is a significant risk factor for ill-health status among the older adults and a major burden on public health. This study unearths the degree of socioeconomic inequalities and assesses the determinants of CoI among the older adults in India.

METHODS

Data on cognitive impairment of older adults aged 60 + years (n = 31,646) gathered in a nationally representative Longitudinal Ageing Study in India (2017-18) was analyzed through STATA with a significance level of 5%. Binary logistic regression, the concentration index, concentration curve, and Shapley decomposition analysis were performed to assess the socioeconomic inequalities and the determinants of CoI.

RESULTS

Sixteen percent of the older adults had CoI. Females (OR = 1.88, 95% CI = 1.70-2.09), those aged 80 plus years (OR = 3.98, 95%CI = 3.56-4.44), from ST (OR = 2.65, 95%CI = 2.32-3.02), with perceived poor health (OR = 1.61,95%CI = 1.45-1.79), with depression (OR = 1.32, 95%CI = 1.21-1.43), with no schooling (OR = 16.46, 95%CI = 11.31-23.97) with 1 + ADL (OR = 1.43, 95%CI = 1.31-1.57) and 1 + IADL (OR = 1.30, 95%CI = 1.19-1.41) had higher odds of CoI than their respective counterparts. Older adults from urban areas (OR = 0.63, 95%CI = 0.57-0.70), higher income groups (OR = 0.61, 95%CI = 0.53- 0.70) and higher education level with sources of financial support (OR = 0.68, 95%CI = 0.61- 0.76) less likely to experience CoI. Economic inequalities exist in the distribution of CoI-the poorest being the most disadvantaged (concentration index value = -0.118).

CONCLUSIONS

There are socioeconomic-related inequalities in CoI among the older adults. The socioeconomically vulnerable older adults, including those illiterates, with poor economic status, women, not-in-union, the older, and those without social support, are more likely to develop CoI. The results suggest awareness generation and more customized policies and programs to reduce the socioeconomic inequalities in CoI among the older adults in India. The improved mental health of the older adults will contribute to achieving Sustainable Development Goals, including Goal 3 on guaranteeing good health and well-being for all.

Measurement and Decomposition of Socioeconomic Inequality in Metabolic Syndrome: A Cross-sectional Analysis of the RaNCD Cohort Study in the West of Iran

OBJECTIVES

Socioeconomic inequality in metabolic syndrome (MetS) remains poorly understood in Iran. The present study examined the extent of the socioeconomic inequalities in MetS and quantified the contribution of its determinants to explain the observed inequality, with a focus on middle-aged adults in Iran.

METHODS

This cross-sectional study used data from the Ravansar Non-Communicable Disease cohort study. A sample of 9975 middle-aged adults aged 35-65 years was analyzed. MetS was assessed based on the International Diabetes Federation definition. Principal component analysis was used to construct socioeconomic status (SES). The Wagstaff normalized concentration index (CIn) was employed to measure the magnitude of socioeconomic inequalities in MetS. Decomposition analysis was performed to identify and calculate the contribution of the MetS inequality determinants.

RESULTS

The proportion of MetS in the sample was 41.1%. The CIn of having MetS was 0.043 (95% confidence interval, 0.020 to 0.066), indicating that MetS was more concentrated among individuals with high SES. The main contributors to the observed inequality in MetS were SES (72.0%), residence (rural or urban, 46.9%), and physical activity (31.5%).

CONCLUSIONS

Our findings indicated a pro-poor inequality in MetS among Iranian middle-aged adults. These results highlight the importance of persuading middle-aged adults to be physically active, particularly those in an urban setting. In addition to targeting physically inactive individuals and those with low levels of education, policy interventions aimed at mitigating socioeconomic inequality in MetS should increase the focus on high-SES individuals and the urban population.

Decomposition analysis of health inequalities between the urban and rural oldest-old populations in China: Evidence from a national survey

The number of Chinese oldest-old (aged 80+) is growing rapidly and some studies have shown that the health status is unequal among older persons in different regions. However, to the best of our knowledge, no study to date has analyzed health inequalities among the oldest-old in urban and rural areas in China. This study therefore aimed to examine the correlation between health inequalities among the oldest-old in urban and rural areas of China. From the 8th wave of the Chinese Longitudinal Health Longevity Survey (CLHLS), we selected 8124 oldest-old participants who met the requirements of the study. Chi-square tests were used to analyze the distribution characteristics of indicators and a logistic model was performed to determine the factors associated with different self-rated health (SRH). The Fairlie model was adopted to decompose the causes and related contributions to health inequality. Our results found that of the Chinese oldest-old, 46.57% were in good health. Urban residents reported significantly better SRH than rural residents (50.17% vs. 45.13%). Variables associated with good and poor SRH had different distribution characteristics. The logistic model suggested that marital status, alcohol consumption, and annual income were important factors underlying the SRH differences. Our decomposition analysis indicated that 76.64% of the SRH differences were caused by observational factors, and validated that the difference in SRH between urban and rural areas was significantly (P<0.05) associated with exercise status (45.44%), annual income (37.64%), social activity status (3.75%), age (-5.27%), and alcohol consumption (-2.66%). Therefore, socioeconomic status and individual lifestyle status were the main factors underlying the health inequality between urban and rural Chinese oldest-old.

Trends and socio-demographic components of modern contraceptive use among sexually active women in Rwanda: a multivariate decomposition analysis

BACKGROUND

The attainment of targets set for modern contraceptive use remains a challenge in sub-Saharan Africa. Rwanda, in its new Family Planning and Adolescent Sexual Reproductive Health/Family Planning (FP/ASRH) Strategic Plan 2018-2024 has set the attainment of a contraceptive prevalence rate (CPR) of 60% by 2024. To achieve this, identifying factors that enhance modern contraceptive use among sexually active women is critical.

METHODS

We used three Rwanda Demographic Health Surveys (RDHS) datasets collected in 2010, 2015, and 2019/2020 in a multivariable decomposition analysis technique to describe trends and identify factors influencing change in modern contraceptive use among sexually active women aged 15-49 years. Results presented as coefficients and percentages took into consideration the complex survey design weighted using StataSE 17.

RESULTS

Modern contraceptive use increased from 40% in 2010 to 52.4% in 2020 among sexually active women. About 23.7% of the overall percentage change in modern contraceptive use was attributable to women's characteristics which included women's education levels, number of living children, and being told about family planning at health facilities. Coefficients contributed 76.26% to the change in modern contraceptive use. This change was attributed to modern contraceptive use among young women between the age of 20-24 years, women's education level, the number of living children, changes in family size, and being visited by community health workers.

CONCLUSION

Rwanda remains on course to archive its 2024 family planning targets. However, there is a need to enhance programs that target sexually active adolescents and young adults, and women from rural areas to sustain the gains made. Furthermore, continuous support of community health workers will be key in exceeding the set targets of modern contraceptive use among sexually active women in Rwanda.

Spatiotemporal distribution and determinants of overweight or obesity among urban women in Ethiopia: a multivariate decomposition analysis

BACKGROUND

Overweight /obesity is a global public health concern. It is higher among women than men in most continents of the world. This study aimed to determine the spatiotemporal distribution and determinants of changes in overweight/obesity over time among urban women in Ethiopia.

METHODS

We used data from three consecutive Demographic and Health Surveys in Ethiopia (2005, 2011, and 2016). The total weighted sample of 1112 in 2005, 3569 in 2011, and 3071 in 2016 urban women were included in the analysis. The primary outcome measure of this study was the spatiotemporal distribution and trends over time in overweight/obesity. Factors contributing to change in overweight/obesity were examined using a logit-based multivariate decomposition analysis.

RESULTS

Overweight/obesity increased from 14.2% in 2005 to 21% in 2016. Approximately 61.3% of the overall increase in overweight/obesity among urban women was due to the difference in coefficient (difference in the effect of characteristics) across the surveys. Changes in the composition of women aged 25-49 years (β = 0.012, 95% CI 0.008, 0.015), married women (β = 0.010, 95% CI 0.006, 0.014), women with formal education (primary: β = 0.007, 95% CI 0.003, 0.011, higher education: β = 0.014, 95% CI 0.006, 0.022), women with formal employment (β = 0.006, 95% CI 0.001, 0.011), and women with informal employment (β = - 0.002, 95% CI - 0.003, - 0.0004) were factors contributing to the change in overweight/obesity from 2005 to 2016. The risk difference (RD) in women's overweight/obesity significantly varied across regions in urban Ethiopia. Furthermore, a high proportion of overweight/obesity was found mainly in Tigray, Oromia, Amhara, and Addis Ababa.

CONCLUSIONS

The rate of overweight/obesity among women in urban Ethiopia has shown a significant increase over the last 11 years. This rate change was due to changes in the composition of women's age, educational status, marital status, and employment status. Therefore, program interventions should be targeted at older (> 25 years), educated, married, Addis Ababa residents, and formally employed women.

Socioeconomic inequalities in teenage pregnancy in Nigeria: evidence from Demographic Health Survey

Background

Despite the high rate of teenage pregnancy in Nigeria and host of negative medical, social and economic consequences that are associated with the problem, relatively few studies have examined socioeconomic inequality in teenage pregnancy. Understanding the key factors associated with socioeconomic inequality in teenage pregnancy is essential in designing effective policies for teenage pregnancy reduction. This study focuses on measuring inequality and identifying factors explaining socioeconomic inequality in teenage pregnancy in Nigeria.

Methods

This is a cross sectional study using individual recode (data) file from the 2018 Nigeria Demographic Health Survey. The dataset comprises a representative sample of 8,423 women of reproductive age 15 – 19 years in Nigeria. The normalized Concentration index (C_n) was used to determine the magnitude of inequalities in teenage pregnancy. The C_n was decomposed to determine the contribution of explanatory factors to socioeconomic inequalities in teenage pregnancy in Nigeria.

Results

The negative value of the C_n (-0.354; 95% confidence interval [CI] = -0.400 to -0.308) suggests that pregnancy is more concentrated among the poor teenagers. The decomposition analysis identified marital status, wealth index of households, exposure to information and communication technology, and religion as the most important predictors contributing to observed concentration of teenage pregnancy in Nigeria.

Conclusion

There is a need for targeted intervention to reduce teenage pregnancy among low socioeconomic status women in Nigeria. The intervention should break the intergenerational cycle of low socioeconomic status that make teenagers’ susceptible to unintended pregnancy. Economic empowerment is recommended, as empowered girls are better prepared to handle reproductive health issues. Moreover, religious bodies, parents and schools should provide counselling, and guidance that will promote positive reproductive and sexual health behaviours to teenagers.

Teenage pregnancy is a global public health concern. It is an undesirable occurrence and seems to be one of the social problems facing several countries, including Nigeria. Previous studies suggest socioeconomic differences in teenage pregnancy in Nigeria. However, relatively few studies have examined the socioeconomic inequality in teenage pregnancy in the country. This study focuses on measuring and explaining predictors of socioeconomic inequality in teenage pregnancy in Nigeria using the Nigeria Demographic Health Survey conducted in 2018. Findings suggest that teenage pregnancy is more concentrated among poor teenagers, while the most important factor contributing to the teenage pregnancy in Nigeria were marital status, wealth index of households, exposure to information and communication technology, and religion. These findings emphasise the need for targeted intervention to reduce teenage pregnancy among low socioeconomic status women in Nigeria to break the intergenerational cycle that expose teenagers to unwanted pregnancy. Since, empowered girls are better prepared to handle reproductive health issues. In addition, religious bodies, parents and schools should give teenagers counselling, and guidance that will promote positive reproductive and sexual health behaviours.

Comparison of end-of-life vehicles management in 31 European countries: A LMDI analysis

In 2018, a total of 6,083,000 end-of-life vehicles (EVLs) with a total weight of 6,732,000 tonnes (including waste parts) were generated in the European Union. These vehicles are a subject of particular attention because of their bulky mass, the hazardous components they contain, and the valuable materials present. This article analyses the quantities of ELVs and parts of ELVs that have been recycled, energy recovered, disposed, and reused to assess the impact of the changes in these management options on the total quantities managed. The analysis covered the statistical data on EVLs in 31 European countries for the period 2006-2018, using a new extended version of the logarithmic mean divisia index (LMDI) analysis model, which allows analysts to compare and analyse different waste management options simultaneously. The results show that the changes in the waste intensities and household final consumption expenditure were the greatest drivers of changes in the total quantities managed, while changes in the quantities recycled, energy recovered, disposed of, and reused had the least impact. All countries met or were close to meeting the targets during the period analysed. Changes in the total quantities of waste managed depended on the economic activity, which influenced the quantities of ELVs generated and their subsequent management.

Trend, multivariate decomposition and spatial variations of unintended pregnancy among reproductive-age women in Ethiopia: evidence from demographic and health surveys

Background

The magnitude of unintended pregnancy is unacceptably high and more than half of it end up with abortions. This may limit lower and middle-income countries to achieve the sustainable development goal targets of reduction of neonatal and maternal mortalities. Evidence on trends and spatial distribution of unintended pregnancy is limited. Therefore, this study aimed to assess the trend, multivariate decomposition, and spatial variations of unintended pregnancy among reproductive-age women in Ethiopia from 2000 to 2016.

Methods

Ethiopian Demographic and Health Data of 2000 to 2016 were used. A total weighted sample of 30,780 reproductive-age women participated. A multivariate decomposition analysis was employed to identify factors contributing to the change in the rate of unintended pregnancy in Ethiopia for 20 years from (1996 to 2016). The concentration index and graph were used to assess wealth-related inequalities, whereas spatial analysis was done to identify the hotspot of unintended pregnancy in Ethiopia.

Results

The 20-year trend analysis showed that the magnitude of unintended pregnancy among reproductive-age women decreased by 13.19 percentage points (from 39.76% in 2000 to 26.57% in 2016 EDHS). About 84.97% of the overall decrement was due to the difference in coefficient of the variables, whereas the remaining 15.03% was due to the difference in composition of the respondent. The differences in coefficient of the variables were decomposed by living metropolitan cities, having previous terminated pregnancy, and not having exposure to media; whereas, the change due to the composition, was expressed by having a household size of 1–3, living in metropolitan cities, being multipara and grand para, being unmarried and having no terminated pregnancy. Moreover, unintended pregnancies were more clustered in Addis Ababa and disproportionately concentrated in the poor groups.

Conclusions

In Ethiopia, a substantial decrement in unintended pregnancy was observed in the past decade. More than four-fifths of this overall decrement was due to the difference in the coefficient of the variables. There was spatial clustering of unintended pregnancy in Ethiopia. A program intervention is needed for high-risk regions such as Addis Ababa. Health education and media campaign should perform for high-risk women such as those having terminated pregnancy, and professing Islam faith.

Supplementary Information

The online version contains supplementary material available at 10.1186/s41182-022-00440-5.

Decomposing the rural-urban gap in the prevalence of undiagnosed, untreated and under-treated hypertension among older adults in India

Background

Although awareness and treatment rates of hypertension have significantly improved in recent years, the prevalence of undiagnosed and untreated hypertension remains a major public health concern for Indian policymakers. While the urban–rural variation in the prevalence, diagnosis, control, and treatment of hypertension is reasonably well-documented, the explanation behind such variation remains poorly understood given the dearth of studies conducted on exploring the determinants of the rural–urban gap in the prevalence of undiagnosed, untreated, and uncontrolled hypertension in India. In view of this research gap, our paper aims to decompose the inter-group differences between rural and urban areas in undiagnosed, untreated, and undertreated hypertension among older adults in India into the major contributing factors.

Methods

Nationally representative data collected in the Longitudinal Ageing Study of India, Wave-1 (2017–18), was utilized for this study. Maximum-likelihood binary logistic-regression models were employed to capture the crude and adjusted associations between the place of residence and prevalence of undiagnosed, untreated, and undertreated hypertension. Fairlie’s decomposition technique was used to decompose the inter-group differences between rural and urban residents in the prevalence of undiagnosed, untreated, and undertreated hypertension among the older population in India, into the major contributing factors, in order to explore the pathways through which these differences manifest.

Results

The overall prevalence rates of undiagnosed, untreated, and undertreated hypertension among older adults were 42.3%, 6%, and 18.7%, respectively. However, the prevalence of undiagnosed and untreated hypertension was higher in rural areas, by 12.4 and 1.7 percentage-points, respectively, while undertreated hypertension was more prevalent in the urban areas (by 7.2 percentage-points). The decomposition analysis explained roughly 41% and 34% of the urban advantage over rural areas in the case of undiagnosed and untreated hypertension, while it explained 51% of the urban disadvantage in respect of undertreated hypertension. The rural–urban differentials in education and comorbidities accounted for the majority of the explained rural disadvantage in the prevalence of undiagnosed hypertension, explaining 13.51% and 13.27% of the gap, respectively. The regional factor was found to be the major driver behind urban advantage in the prevalence of untreated hypertension, contributing 37.47% to the overall gap. In the case of undertreated hypertension, education, comorbidities, and tobacco consumption were the major contributors to the urban–rural inequality, which accounted for 12.3%, 10.6%, and 9.8% of the gap, respectively.

Conclusion

Socio-economic and lifestyle factors seemed to contribute significantly to the urban–rural gap in undiagnosed, untreated and undertreated hypertension in India among older adults. There is an urgent need of creating awareness programmes for the early identification of hypertensive cases and regular treatment, particularly in under-serviced rural India. Interventions should be made targeting specific population groups to tackle inequality in healthcare utilization.

The driving factors and future changes of CO2 emission in China's nonferrous metal industry

As an energy-intensive industry in China, it is critical to promote energy conservation and carbon emission reduction in the nonferrous metal industry (NMI). This study first applies the Tapio decoupling model to explore the relationships between the industrial output and CO₂ emission in China's NMI. Then, the Generalized Divisia Index Model (GDIM) is adopted to uncover the factors driving the changes in CO₂ emission from 2000 to 2019, and based on the decomposition results, scenario analysis is used to predict potential CO₂ emission during 2021-2035. The results show that (1) the CO₂ emission in China's NMI increases by 397.93 million tons (Mt) during 2000-2019, and the decoupling state between the industrial output and CO₂ emission is characterized by the weak decoupling status; (2) overall, the output scale is the dominant factor promoting the CO₂ emissions increase, followed by the investment scale and energy consumption scale, while the carbon intensity of output and the carbon intensity of investment are the two most important abatement factors; (3) the scenario analysis indicates that the CO₂ emission from NMI will peak around 2030 under the low-carbon scenario while 2026 under the enhanced low-carbon scenario. Policy suggestions are further put forward for carbon emission reduction in China's NMI.