National-level Analysis Research Articles

Spatial–Temporal Characteristics, Source Apportionment, and Health Risks of Atmospheric Volatile Organic Compounds in China: A Comprehensive Review

Volatile organic compounds (VOCs) are ubiquitous in the atmosphere, posing significant adverse impacts on air quality and human health. However, current research on atmospheric VOCs mainly focuses on specific regions or industries, without comprehensive national-level analysis. In this study, a total of 99 articles on atmospheric VOCs in China published from 2015 to 2024 were screened, and data on their concentrations, source apportionment, and health risks were extracted and summarized. The results revealed that the annual average concentrations of TVOCs and their groups in China generally increased and then decreased between 2011 and 2022, peaking in 2018–2019. A distinct seasonal pattern was observed, with the highest concentrations occurring in winter, followed by autumn, spring, and summer. TVOC emissions were highly concentrated in northern and eastern China, mainly contributed by alkanes and alkenes. Source apportionment of VOCs indicated that vehicle sources (32.9% ± 14.3%), industrial emissions (18.0% ± 12.8%), and other combustion sources (13.0% ± 13.0%) were the primary sources of VOCs in China. There was a significant positive correlation (p < 0.05) between the annual mean VOC concentration and population size, and a notable negative correlation (p < 0.05) with GDP per capita. Atmospheric VOCs had no non-carcinogenic risk (HI = 0.5) but exhibited a probable carcinogenic risk (7.5 × 10−5), with relatively high values for 1,2-dibromoethane, 1,2-dichloroethane, and naphthalene. The health risk was predominantly driven by halocarbons. These findings are essential for a better understanding of atmospheric VOCs and for developing more targeted VOC control measures.

The Immigrant Mortality Advantage Among Over-65 Middle Eastern and North African Immigrants to the United States.

Immigrants to the United States often have longer life expectancies than their U.S.-born counterparts, however it is unclear whether a similar "immigrant advantage" exists for immigrants from the Middle East and North Africa (MENA). This study uses a novel machine-learning name classifier to offer one of the first national-level examinations of MENA mortality patterns by nativity in the United States. A recurrent neural network model was developed to identify MENA individuals based on given name and surname characteristics. The model was trained on more than 2.5 million mortality-linked social security records in the Berkeley Unified Numident Mortality Database (BUNMD). Mortality rates and life expectancy were estimated using a Gompertz distribution and maximum likelihood estimation, focusing on high-coverage years between 1988 and 2005 and deaths over age 65. Foreign-born MENA men over 65 showed a significant immigrant mortality advantage with a hazard ratio (HR) of 0.64 and an estimated 3.13 additional years of life expectancy at age 65 compared to U.S.-born counterparts. Foreign-born MENA women also exhibited an advantage, with a HR of 0.71 and an additional 2.24years of life expectancy at age 65. This study is one of the first national-level analyses of mortality outcomes among the over-65 MENA population in the United States, finding a MENA immigrant mortality advantage. The results suggest further research is needed to identify and disaggregate the MENA population in health research.

Development of an Auxiliary Indicator for Improving the Rationality and Reliability of the National-Level Carbon Productivity Indicator

Global attention to climate change has surged since the advent of the Paris Agreement, intensifying the importance of measuring and managing carbon productivity indicators on a national level. Nevertheless, concerns persist regarding the reliability of such measurements because of inherent discrepancies in implementing and operating national-level carbon productivity indicators, coupled with their inherent uncertainty. This study proposes a multiple regression model to address these issues aimed at refining national-level carbon productivity indicator metrics, accounting for factors such as the gross domestic product and total greenhouse gas emissions by sectors. The objective was to offer insights into enhancing and effectively utilizing current indicators, enabling a more nuanced interpretation of the variation in the carbon productivity indicators across diverse industrial landscapes. This study showed that adjustments of the carbon productivity metrics reflect disparities in emissions across industrial structures, with countries characterized by high emissions from non-service industries showing improving trends. In addition, this paper proposes an auxiliary indicator estimating method for carbon productivity that, when utilized with current methodologies, is more usable to interpret productivity indicators within the context of varying industrial compositions across OECD countries. Moreover, by elucidating the nuances of industrial structures, this study advocates for more sophisticated approaches to interpreting and managing the productivity indicators tailored to the unique economic landscape of each country. Nevertheless, the limitations stemming from data availability underscore the need for further research, particularly in refining the national-level carbon resource productivity indicators analyses and exploring the thematic productivity variations in greater depth. By addressing these gaps, future studies will contribute to a more comprehensive understanding of national-level carbon resource productivity indicators dynamics and reveal targeted strategies for sustainable development.

Do typhoon disasters foster climate change concerns? Evidence from public discussions on social media in China

Combating the adverse impacts of extreme climate events through adaptation depends on climate change awareness from both governments and the public. It has long been discussed that historical experiences of climatic hazards might help to foster and raise public concerns about climate change, and consequently contribute to climate actions. However, current studies have reached no consensus on the impacts of the occurrence of extreme climatic hazards on the public's climate change awareness. This study provides a national-level analysis of climate change-related posts accompanying extreme typhoon events in China from 2011 to 2022, based on social media big data and machine learning, to discern the relationship between occurrences of typhoon disasters and climate change concerns on Weibo—in terms of the volume, contents and sentiment expressed in climate change-related posts. Our analysis found that the volume of climate change-related posts generally did not significantly increase during or after typhoon disasters. In terms of contents, though, the proportion of contents about climate change impacts did significantly increase during typhoon events, from 41.74 % to 48.97 %, and these disasters also significantly provoked negative sentiment toward climate change, which increased from 62.47 % to 70.18 %. Contents about climate change impacts and negative sentiment, however, were observed to bounce back to pre-disaster levels within about twelve days after typhoon events. Our study emphasizes the importance of learning from previous climatic disasters, to foster public concerns about climate change and thereby to promote climate actions.

Emerging trends in research on perineal trauma management: A bibliometric analysis of articles published since 1985

BackgroundThe purpose of this bibliometric analysis is to explore global trends in scientific research involving spontaneous perineal tears sustained during childbirth. This research is critical as a significant number of women have vaginal lacerations after birth resulting in complications such as pain and pelvic floor dysfunction. MethodsThe articles used in this bibliometric analysis were collected from PubMed, Web of Science, Cochrane library and Scopus. Analysis was carried out in Python and R programming languages with some visualizations created using VOS software. Apart from traditional methods, this analysis also involved time series forecasting and assessment of rolling correlations. ResultsResults indicate authors and institutions from the United Kingdom as the most productive in the research on this subject research. National level analyses for six countries showed that productivity was positively correlated with GDP/capita, average health expenditure and negatively associated with proportion of C-sections. Recent and emerging themes include those involving pharmacological interventions for pain management. ConclusionThere is a growing global interest in the research on postnatal perineal trauma with authors from the UK playing a leading role so far. Countries with high vaginal birth rates, need to promote research in this field to minimise trauma-associated comorbidities.

Improving the prescriptive appropriateness of vitamin D: The Italian experience

At the Asl Napoli 3 SUD a local, regional and national level analysis of prescription and spending related to the prescription and dispensing of drugs intended to increase vitamin D levels in the human body was carried out. The Italian Pharmacy Regulatory Agency (AIFA) in late 2019 introduced a prescriptive note of appropriateness (note 96) to regulate the prescribing activity of a drug that is widely used on the Italian national population, significantly affecting spending by the National Health System (NHS). Despite this action there has been an increase in prescription and expenditure of calcifediol at all levels of analysis (national, regional and local) while regarding the remaining Anatomical Therapeutic Chemical (ATC) referring to drugs used as vitamin D supplement in the Campania Region and at the Asl Napoli 3 SUD there is a slower decrease in expenditure and prescription, sometimes even increasing and in countertendency to the Italian national average. For these reasons, the Campania Region instituted two executive decrees (DD 405/2021 and 91/2022) that led to a marked reduction in spending and prescription in 2022 even higher than in other Italian regional realities. This analysis aims to show how vitamin D prescription is widespread and often inappropriate, attested by wide regional variability. In addition, the main recommendations for the use of these drugs are highlighted in order to raise awareness among all healthcare professionals of the informed use of these molecules ensuring sustainability and governance.

Tuberculosis case notifications and outcomes in Peruvian prisons prior to and during the COVID-19 pandemic: a national-level interrupted time series analysis

Tuberculosis case notifications and outcomes in Peruvian prisons prior to and during the COVID-19 pandemic: a national-level interrupted time series analysis

Comparing energy system optimization models and integrated assessment models: Relevance for energy policy advice.

The transition to a climate neutral society such as that envisaged in the European Union Green Deal requires careful and comprehensive planning. Integrated assessment models (IAMs) and energy system optimisation models (ESOMs) are both commonly used for policy advice and in the process of policy design. In Europe, a vast landscape of these models has emerged and both kinds of models have been part of numerous model comparison and model linking exercises. However, IAMs and ESOMs have rarely been compared or linked with one another. This study conducts an explorative comparison and identifies possible flows of information between 11 of the integrated assessment and energy system models in the European Climate and Energy Modelling Forum. The study identifies and compares regional aggregations and commonly reported variables. We define harmonised regions and a subset of shared result variables that enable the comparison of scenario results across the models. The results highlight how power generation and demand development are related and driven by regional and sectoral drivers. They also show that demand developments like for hydrogen can be linked with power generation potentials such as onshore wind power. Lastly, the results show that the role of nuclear power is related to the availability of wind resources. This comparison and analysis of modelling results across model type boundaries provides modellers and policymakers with a better understanding of how to interpret both IAM and ESOM results. It also highlights the need for community standards for region definitions and information about reported variables to facilitate future comparisons of this kind. The comparison shows that regional aggregations might conceal differences within regions that are potentially of interest for national policy makers thereby indicating a need for national-level analysis.

Monthly Analysis of Infant Mortality Rate in Portugal during the COVID-19 Pandemic: Insights from Continuous Monitoring.

The COVID-19 pandemic significantly impacted global public health. Infant mortality rate (IMR), a vital statistic and key indicator of a population's overall health, is essential for developing effective health prevention programs. Existing evidence primarily indicates a decrease in IMR during the COVID-19 pandemic. We conducted a national-level analysis to calculate IMR and describe its course over the years (from 2016 until 2022), using a month-by-month analysis. Data on the number of deaths under one year of age was collected from the Portuguese E-Death Certification System (SICO), and data on the number of monthly live births was obtained from Statistics Portugal. The IMR was calculated per month, considering the previous 12 months' cumulative number of deaths under one year of age and the number of live births. In Portugal, the IMR decreased before and during the COVID-19 pandemic. The lowest values were observed in September and October 2021 (2.15 and 2.14 per 1000 live births, respectively). The IMR remained below the threshold of three deaths per 1000 live births during the pandemic's critical period. Portugal has achieved remarkable progress in reducing its IMR over the last 60 years. The country recorded its lowest-ever IMR values during the COVID-19 pandemic. Further studies are needed to fully understand the observed trends.

Pregnancy following assisted reproductive technology in morbidly obese patients: assessment of feto-maternal outcomes

PurposeTo examine feto-maternal characteristics and outcomes of morbidly obese pregnant patients who conceived with assisted reproductive technology (ART).MethodsThis cross-sectional study queried the Healthcare Cost and Utilization Project’s National Inpatient Sample. Study population was 48,365 patients with ART pregnancy from January 2012 to September 2015, including non-obesity (n = 45,125, 93.3%), class I–II obesity (n = 2445, 5.1%), and class III obesity (n = 795, 1.6%). Severe maternal morbidity at delivery per the Centers for Disease and Control Prevention definition was assessed with multivariable binary logistic regression model.ResultsPatients in the class III obesity group were more likely to have a hypertensive disorder (adjusted-odds ratio (aOR) 3.03, 95% confidence interval (CI) 2.61–3.52), diabetes mellitus (aOR 3.08, 95%CI 2.64–3.60), large for gestational age neonate (aOR 3.57, 95%CI 2.77–4.60), and intrauterine fetal demise (aOR 2.03, 95%CI 1.05–3.94) compared to those in the non-obesity group. Increased risks of hypertensive disease (aOR 1.35, 95%CI 1.14–1.60) and diabetes mellitus (aOR 1.39, 95%CI 1.17–1.66) in the class III obesity group remained robust even compared to the class I–II obesity group. After controlling for priori selected clinical, pregnancy, and delivery factors, patients with class III obesity were 70% more likely to have severe maternal morbidity at delivery compared to non-obese patients (8.2% vs 4.4%, aOR 1.70, 95%CI 1.30–2.22) whereas those with class I–II obesity were not (4.1% vs 4.4%, aOR 0.87, 95%CI 0.70–1.08).ConclusionsThe results of this national-level analysis in the United States suggested that morbidly obese pregnant patients conceived with ART have increased risks of adverse fetal and maternal outcomes.

A comparative national-level analysis of government food system resilience activities across four developed countries at varying stages of planning

BackgroundThe COVID-19 pandemic, extreme weather events, and the Russian invasion of Ukraine have highlighted global food system vulnerabilities and a lack of preparedness and prospective planning for increasingly complex disruptions. This has spurred an interest in food system resilience. Despite the elevated interest in food system resilience, there is a lack of comparative analyses of national-level food system resilience efforts. An improved understanding of the food system resilience landscape can support and inform future policies, programs, and planning.MethodsWe conducted a cross-country comparison of national-level food system resilience activities from Australia, Aotearoa New Zealand, Sweden, and the United States. We developed upon and adapted the resilience framework proposed by Harris and Spiegel to compare actions derived from thirteen national food system resilience documents. We coded the documents based on the actions taken by the governments including: the food system resilience attributes utilized, the part of the food supply chain, the specific shocks or stressors, the implementation level, the temporal focus of action, and the expected impact on food security. We analyzed and compared countries’ coded categories and subcategories, and category combinations.ResultsThe results showed that these countries are addressing some of the same issues, are using multi-pronged policy actions to address food system resilience issues, and are focused on both retrospective reviews and prospective models of disruptive events to inform their decisions. Some work has been done towards preparing for climate change and other natural disasters, and less preparing has been done for other shocks or stressors.ConclusionsThis paper develops and applies a framework rooted in literature to understand the content of national-level food system resilience documents. The analysis identified potential gaps, concentrations, and themes in national food systems resilience. The framework can be applied to augment existing policy, create new policy, as well as to supplement and complement other existing frameworks.

Measuring social-emotional development in schoolchildren: A national-level analysis of ECLS-B cohort data

The present study examined the social-emotional development items assessed by kindergarten teachers in the Early Childhood Longitudinal Study-Birth Cohort to determine the optimal factor structure underlying the items as well as the reliability and validity of the resulting factors. This study identified an empirically derived factor structure for teacher-reported social development, investigated whether there was evidence of bias in teacher assessments of social-emotional constructs, examined factor invariance across demographic characteristics (i.e., race and ethnicity, sex, and poverty status), and examined the external validity of the derived factors by determining the extent to which they were associated with well-established measures of early childhood competencies. Findings suggested a 4-factor solution was optimal, consisting of (a) Interpersonal Skills, (b) Externalizing Behavior, (c) Approaches to Learning, and (d) Perspective Taking. Findings offer suggestive evidence of teacher biases in assessments and some, although not conclusive, support for the invariance of social-emotional dimension across demographic characteristics. Results provide a useful next step toward documenting reliable and valid social-emotional measures for use in early childhood research and challenges users of national datasets to think critically about the use of “scales” without a priori attention to important psychometric properties.

The EU’s human security based approach towards energy poverty

The phenomenon of energy poverty shows that energy issues, traditionally linked with international, regional, and national levels of analysis, have wider economic and political causes that are being manifested at the community and individual levels as well. Latest energy crisis across the European continent, coped with some structural factors such are resource scarcity, energy transition, and war between Russia and Ukraine, emphasized individualistic consequences of the ongoing energy processes. The fact that approximately 42 million people in the EU are affected by energy poverty put the phenomenon of the energy poverty very high at the EU agenda. Clear connection of this topic with human security concept made the phenomenon of energy poverty justifiable to be analysed from the people-centred perspective. Therefore, the goal of this paper is to highlight human security approach as a solid framework for understanding and analysis of the energy poverty phenomenon in the EU. Review of the significant academic knowledge base on this phenomenon, secondary data analysis from the relevant European surveys related to this issue, and analysis of adequate EU policies and practices combating energy poverty will serve to outline state-of-playwhen it comes to the energy poverty and human security nexus at the EU level.

Impact of connective tissue diseases on inpatient outcomes in gastrointestinal bleeding: insights from a national database analysis.

Connective tissue diseases (CTDs) are characterized by immune system dysregulation, which can profoundly impact the gastrointestinal (GI) system. While GI bleeding is a well-recognized cause of mortality and morbidity in the USA, its occurrence in patients with CTD remains documented but underexplored in terms of inpatient outcomes. GI bleeding in CTD is attributed to factors such as vasculopathy and drug-related risks, notably steroids and non-steroidal anti-inflammatory drugs (NSAIDs). This research seeks to conduct a comprehensive national-level analysis, utilizing the National Inpatient Sample (NIS), to compare GI bleeding outcomes between patients with CTD and those without this condition. Utilizing the extensive NIS database covering 2020, we conducted a retrospective analysis of GI bleeding patients with CTD, identified through the International Classification of Diseases, 10th Revision (ICD-10). The primary outcome was in-hospital mortality. The secondary outcomes included rate of urgent esophagogastroduodenoscopy (EGD) and colonoscopy-endoscopy in 1 day or less, total rate of EGD and colonoscopy, rate of EGD and Colonoscopy with intervention, rate of complications including acute kidney injury (AKI), blood transfusion, sepsis, pneumonia, pulmonary embolism (PE) and healthcare utilization. Employing Stata software, we utilized multivariate logistic and linear regression analyses to adjust for confounders. There were 455,494 hospitalizations for GI bleeding and 19,874 involved patients with CTDs. The in-hospital mortality rate was significantly lower for CTD patients at 2.1%, compared to 2.4% for non-CTD patients [adjusted odds ratio (aOR): 0.79, 95% confidence interval (CI): 0.63-0.99, P=0.04]. CTD patients showed increased odds of total EGD, urgent colonoscopy, and total colonoscopy; however, these changes were not statistically significant. CTD patients had higher odds of complications, including PE (6.87% vs. 4.12%, P=0.009). However, there were no significant differences in mean length of hospital stay and total hospital charges (THCs) compared to non-CTD patients. Patients with CTD exhibited a lower in-hospital mortality rate compared to those without CTD. The elevated risk of PE underscores the importance of implementing prophylactic measures for these patients.

Elaborated Framework for Duplicate Device Detection from Multisourced Mobile Device Location Data

Mobile device location data (MDLD) have been popularly utilized in various fields. Yet large-scale applications are limited because of either biased or insufficient spatial coverage of the data from individual data vendors. One approach to improve the data coverage is to leverage the data from different data vendors and integrate them to build a more representative dataset. To extract reliable statistics from MDLD, certain data preprocessing steps are crucial to ensure the accuracy of the analysis. One of these steps is the development of a framework to remove duplicated devices or several devices that belong to the same data subject. This treatment is especially necessary when using a multiplicity of data sources, as the same device may be captured by more than one data provider. We propose a data integration methodology for multisourced data to investigate the feasibility of integrating data from several sources. By leveraging the uniqueness of travel pattern of each device, duplicate devices are identified. The proposed methodology is shown to be cost-effective through a national-level analysis. The method is successfully applied to a dataset from January 2020 consisting of more than 270 million raw devices nationwide. Our findings suggest that devices sharing the same imputed home location and the same top-five most-visited locations during a month can represent the same user in the MDLD. It is shown that more than 99.6% of the sample devices having the aforementioned attribute in common are observed at the same location simultaneously.

Patient safety incidents in endoscopy: a human factors analysis of nonprocedural significant harm incidents from the National Reporting and Learning System (NRLS).

Despite advances in understanding and reducing the risk of endoscopic procedures, there is little consideration of the safety of the wider endoscopy service. Patient safety incidents (PSIs) still occur. We sought to identify nonprocedural PSIs (nPSIs) and their causative factors from a human factors perspective and generate ideas for safety improvement. Endoscopy-specific PSI reports were extracted from the National Reporting and Learning System (NRLS). A retrospective, cross-sectional human factors analysis of data was performed. Two independent researchers coded data using a hybrid thematic analysis approach. The Human Factors Analysis and Classification System (HFACS) was used to code contributory factors. Analysis informed creation of driver diagrams and key recommendations for safety improvement in endoscopy. From 2017 to 2019, 1181 endoscopy-specific PSIs of significant harm were reported across England and Wales, with 539 (45.6%) being nPSIs. Five categories accounted for over 80% of all incidents, with "follow-up and surveillance" being the largest (23.4% of all nPSIs). From the free-text incident reports, 487 human factors codes were identified. Decision-based errors were the most common act prior to PSI occurrence. Other frequent preconditions to incidents were focused on environmental factors, particularly overwhelmed resources, patient factors, and ineffective team communication. Lack of staffing, standard operating procedures, effective systems, and clinical pathways were also contributory. Seven key recommendations for improving safety have been made in response to our findings. This was the first national-level human factors analysis of endoscopy-specific PSIs. This work will inform safety improvement strategies and should empower individual services to review their approach to safety.

The association of maternal obesity and obstetric anal sphincter injuries at time of vaginal delivery

The risk of third- and fourth-degree perineal laceration after vaginal delivery in patients with obesity is relatively understudied and has mixed findings in existing literature. This study aimed to examine the association of maternal obesity and obstetric anal sphincter injuries at vaginal delivery. The Healthcare Cost and Utilization Project's National Inpatient Sample was retrospectively queried to examine 7,385,341 vaginal deliveries from January 2017 to December 2019. The exposure assignment was obesity status. The main outcomes were third- and fourth-degree perineal lacerations after vaginal delivery. Statistical analysis examining the exposure-outcome association included (1) inverse probability of treatment weighting with log-Poisson regression generalized linear model to account for prepregnant and pregnant confounders for the exposure and (2) multinomial regression model to account for delivery factors in the inverse probability of treatment weighting cohort. The secondary outcomes included (1) the temporal trends of fourth-degree laceration and its associated factors at cohort level and (2) risk factor patterns for fourth-degree laceration by constructing a classification tree model. In the inverse probability of treatment weighting cohort, patients with obesity were less likely to have fourth-degree lacerations and third-degree lacerations than patients without obesity (fourth-degree laceration: 2.3 vs 3.9 per 1000 vaginal deliveries, respectively; adjusted odds ratio, 0.62; 95% confidence interval, 0.56-0.69; third-degree laceration: 15.6 vs 20.1 per 1000 vaginal deliveries, respectively; adjusted odds ratio, 0.79; 95% confidence interval, 0.76-0.82). In contrast, in patients with obesity vs those without obesity, forceps delivery (54.7 vs 3.3 per 1000 vaginal deliveries, respectively; adjusted odds ratio, 17.73; 95% confidence interval, 16.17-19.44), vacuum-assisted delivery (19.8 vs 2.9 per 1000 vaginal deliveries, respectively; adjusted odds ratio, 5.18; 95% confidence interval, 4.85-5.53), episiotomy (19.2 vs 2.8 per 1000 vaginal deliveries, respectively; adjusted odds ratio, 3.95; 95% confidence interval, 3.71-4.20), and shoulder dystocia (17.8 vs 3.4 per 1000 vaginal deliveries, respectively; adjusted odds ratio, 2.60; 95% confidence interval, 2.29-2.94) were associated with more than a 2-fold increased risk of fourth-degree perineal laceration. Among the group with obesity, patients who had forceps delivery and shoulder dystocia had the highest incidence of fourth-degree laceration (105.3 per 1000 vaginal deliveries). Among the group without obesity, patients who had forceps delivery, shoulder dystocia, and macrosomia had the highest incidence of fourth-degree laceration (294.1 per 1000 vaginal deliveries). The incidence of fourth-degree perineal laceration decreased by 11.9% over time (P trend=.004); moreover, forceps delivery, vacuum-assisted delivery, and episiotomy decreased by 3.8%, 7.6%, and 29.5%, respectively (all, P trend<.05). This national-level analysis suggests that patients with obesity are less likely to have obstetric anal sphincter injuries at the time of vaginal delivery. Furthermore, this analysis confirms other known risk factors for fourth-degree laceration, such as forceps delivery, vacuum-assisted delivery, episiotomy, and shoulder dystocia. However, we noted a decreasing trend in fourth-degree lacerations, which may be due to evolving obstetrical practices.

‘Forest malaria’ in Myanmar? Tracking transmission landscapes in a diversity of environments

BackgroundIn the Greater Mekong Subregion, case–control studies and national-level analyses have shown an association between malaria transmission and forest activities. The term ‘forest malaria’ hides the diversity of ecosystems in the GMS, which likely do not share a uniform malaria risk. To reach malaria elimination goals, it is crucial to document accurately (both spatially and temporally) the influence of environmental factors on malaria to improve resource allocation and policy planning within given areas. The aim of this ecological study is to characterize the association between malaria dynamics and detailed ecological environments determined at village level over a period of several years in Kayin State, Myanmar.MethodsWe characterized malaria incidence profiles at village scale based on intra- and inter-annual variations in amplitude, seasonality, and trend over 4 years (2016–2020). Environment was described independently of village localization by overlaying a 2-km hexagonal grid over the region. Specifically, hierarchical classification on principal components, using remote sensing data of high spatial resolution, was used to assign a landscape and a climate type to each grid cell. We used conditional inference trees and random forests to study the association between the malaria incidence profile of each village, climate and landscape. Finally, we constructed eco-epidemiological zones to stratify and map malaria risk in the region by summarizing incidence and environment association information.ResultsWe identified a high diversity of landscapes (n = 19) corresponding to a gradient from pristine to highly anthropogenically modified landscapes. Within this diversity of landscapes, only three were associated with malaria-affected profiles. These landscapes were composed of a mosaic of dense and sparse forest fragmented by small agricultural patches. A single climate with moderate rainfall and a temperature range suitable for mosquito presence was also associated with malaria-affected profiles. Based on these environmental associations, we identified three eco-epidemiological zones marked by later persistence of Plasmodium falciparum, high Plasmodium vivax incidence after 2018, or a seasonality pattern in the rainy season.ConclusionsThe term forest malaria covers a multitude of contexts of malaria persistence, dynamics and populations at risk. Intervention planning and surveillance could benefit from consideration of the diversity of landscapes to focus on those specifically associated with malaria transmission.Graphical

Equity assessment of maternal and child healthcare benefits utilization and distribution in public healthcare facilities in Bangladesh: a benefit incidence analysis

BackgroundThe distribution of healthcare services should be based on the needs of the population, regardless of their ability to pay. Achieving universal health coverage implies first ensuring that people of all income levels have access to quality healthcare, and then allocating resources reasonably considering individual need. Hence, this study aims to understand how public benefits in Bangladesh are currently distributed among wealth quintiles considering different layers of healthcare facilities and to assess the distributional impact of public benefits.MethodsTo conduct this study, data were extracted from the recent Bangladesh Demographic and Health Survey 2017–18. We performed benefit incidence analysis to determine the distribution of maternal and child healthcare utilization in relation to wealth quintiles. Disaggregated and national-level public benefit incidence analysis was conducted by the types of healthcare services, levels of healthcare facilities, and overall utilization. Concentration curves and concentration indices were estimated to measure the equity in benefits distribution.ResultsAn unequal utilization of public benefits observed among the wealth quintiles for maternal and child healthcare services across the different levels of healthcare facilities in Bangladesh. Overall, upper two quintiles (richest 19.8% and richer 21.7%) utilized more benefits from public facilities compared to the lower two quintiles (poorest 18.9% and poorer 20.1%). Benefits utilization from secondary level of health facilities was highly pro-rich, while benefit utilization found pro-poor at primary levels. The public benefits in Bangladesh were also not distributed according to the needs of the population; nevertheless, poorest 20% household cannot access 20% share of public benefits in most of the maternal and child healthcare services even if we ignore their needs.ConclusionsBenefit incidence analysis in public health spending demonstrates the efficacy with which the government allocates constrained health resources to satisfy the needs of the poor. Public health spending in Bangladesh on maternal and child healthcare services were not equally distributed among wealth quintiles. Overall health benefits were more utilized by the rich relative to the poor. Hence, policymakers should prioritize redistribution of resources by targeting the socioeconomically vulnerable segments of the population to increase their access to health services to meet their health needs.

Spatial and temporal trends of overweight/obesity and tobacco use in East Africa: subnational insights into cardiovascular disease risk factors

BackgroundCardiovascular disease (CVD) is increasing in Sub-Saharan Africa (SSA). Overweight/obesity and tobacco use are modifiable CVD risk factors, however literature about the spatiotemporal dynamics of these risk factors in the region at subnational or local scales is lacking. We describe the spatiotemporal trends of overweight/obesity and tobacco use at subnational levels over a 13-year period (2003 to 2016) in five East African nations.MethodsCross-sectional, nationally representative Demographic and Health Surveys (DHS) were used to explore the subnational spatiotemporal patterns of overweight/obesity and tobacco use in Burundi, Kenya, Rwanda, Tanzania, and Uganda, five East African Community (EAC) nations with unique cultural landscapes influencing CVD risk factors. Adaptive kernel density estimation and logistic regression were used to determine the spatial distribution and change over time of CVD risk factors on a subnational and subpopulation (rural/urban) scale.ResultsSubnational analysis shows that regional and national level analysis masks important trends in CVD risk factor prevalence. Overweight/obesity and tobacco use trends were not similar: overweight/obesity prevalence increased across most nations included in the study and the inverse was true for tobacco use prevalence. Urban populations in each nation were more likely to be overweight/obese than rural populations, but the magnitude of difference varied widely between nations. Spatial analysis revealed that although the prevalence of overweight/obesity increased over time in both urban and rural populations, the rate of change differed between urban and rural areas. Rural populations were more likely to use tobacco than urban populations, though the likelihood of use varied substantially between nations. Additionally, spatial analysis showed that tobacco use was not evenly distributed across the landscape: tobacco use increased in and around major cities and urban centers but declined in rural areas.ConclusionsWe highlight the importance of de-homogenizing CVD risk factor research in SSA. Studies of national or regional prevalence trends mask important information about subpopulation and place-specific behavior and drivers of risk factor prevalence. Spatially explicit studies should be considered as a vital tool to understand local drivers of health, disease, and associated risk factor trends, especially in highly diverse yet low-resourced, marginalized, and often homogenized regions.