Caries status in 12-year-old children, geographical location and socioeconomic conditions across European countries: A systematic review and meta-analysis.

BACKGROUND: Understanding of socioeconomic context might enable more efficient evidence-based preventive strategies in oral health. AIM: The study assessed the caries-related socioeconomic macro-factors in 12-year-olds across European countries. DESIGN: This systematic review involved epidemiological surveys on the caries status of 12-year-olds from 2011 to 2022. DMFT was analyzed in relation to gross national income (GNI), United Nations Statistical Division geographical categorization of European countries (M49), unemployment rate, Human Development Index (HDI), and per capita expenditure on dental health care. A meta-analysis was performed for countries reporting data on DMFT, stratified by GNI, and geographical location of European countries, using a random-effects model. RESULTS: The study involved 493 360 children from 36 countries in the geographic region of Europe. The analysis confirmed a strong negative correlation between income and caries experience (p < .01). Children living in higher-income countries showed 90% lower odds of poor oral health than in middle-income countries. Children living in West Europe showed 90% lower odds of poor oral health than children living in East Europe. CONCLUSION: The strong effect of macro-level socioeconomic contexts on children's oral health suggests favoring upstream preventive oral health strategies in countries with economic growth difficulties, Eastern and Southern parts of Europe.

Racial and ethnic differences in uncontrolled diabetes mellitus among adults taking antidiabetic medication.

AIM: To examine whether racial and ethnic disparities in uncontrolled type 2 diabetes mellitus (T2DM) persist among those taking medication and after accounting for other demographic, socioeconomic, and health indicators. METHODS: Adults aged ≥20 years with T2DM using prescription diabetes medication were among participants assessed in a retrospective cohort study of the National Health and Nutrition Examination Survey 2007-2018. We estimated weighted sequential multivariable logistic regression models to predict odds of uncontrolled T2DM (HbA1c ≥ 8%) from racial and ethnic identity, adjusting for demographic, socioeconomic, and health indicators. RESULTS: Of 3649 individuals with T2DM who reported taking medication, 27.4% had uncontrolled T2DM (mean HgA1c 9.6%). Those with uncontrolled diabetes had a mean BMI of 33.8, age of 57.3, and most were non-Hispanic white (54%), followed by 17% non-Hispanic Black, and 20% Hispanic identity. In multivariable analyses, odds of uncontrolled T2DM among those with Black or Hispanic identities lessened, but persisted, after accounting for other indicators (Black OR 1.38, 97.5% CI: 1.04, 1.83; Hispanic OR 1.79, 97.5% CI 1.25, 2.57). CONCLUSIONS: Racial and ethnic disparities in T2DM control persisted among individuals taking medication. Future research might focus on developmental and epigenetic pathways of disparate T2DM control across racially and ethnically minoritized populations.

Human mobility and socioeconomic datasets of the Rio de Janeiro metropolitan area.

This data descriptor presents two main datasets and a set of auxiliary files. The mobility dataset presents a long-term study of human mobility in the Rio de Janeiro Metropolitan Area (RJMA) performed in the entire year of 2014 based on mobile phone data. The socioeconomic dataset presents selected socioeconomic variables of the Brazilian 2010 census. A set of auxiliary files is included to present georeferenced information and geographic features (shapefiles) and data used to validate the mobility estimates. The human mobility estimation was carried out using a methodology that allows direct integration with census data, based on an approximation of the geographic boundaries of census units by an aggregation of Voronoi polygons of the mobile phone antennas. The study area is the Brazilian local area 21, which includes the entire RJMA and four other municipalities. The mobility dataset is divided into two files: one is an estimation of the origin-destination (OD) matrix per day, and the other is a visitors' dataset where the number of visitors of each location is estimated in four shifts each day. The socioeconomic dataset presents information of 55 variables for each location, which have been used in different studies and present the longest human mobility dataset available for public use.

Equal in ashes? Exploring socioeconomic inequalities in lifespan based on obituary data in Austria.

Understanding the emergence of and changes in socioeconomic inequalities in lifespan requires reliable, longitudinal data. In the absence of administrative data, published obituaries may be one such alternative source. With the validity of drawing relevant data from obituaries not yet established in population health research, this study addresses this gap by estimating socioeconomic inequalities in lifespan in Vorarlberg, Austria. Data for all individuals (n = 1490) with obituaries published (July to December 2022) in a regional newspaper (market share: 56%) were extracted, including different markers of the deceased's socioeconomic status. Linear regression analyses showed that, on average, individuals with medium-sized obituaries lived 6.02 years (95% CI: 4.19, 7.85) and individuals with the largest obituaries 12.04 years (95% CI: 7.04, 17.04) longer than individuals with small obituaries while blue-collar workers lived 10.50 years (95% CI: -14.51, -6.49) shorter than individuals with no occupation (reported). This socioeconomic gradient is in line with findings based on national data sources, and comparisons with official regional data are promising regarding data representativeness and completeness. With obituary size reflecting different costs (€210-€1626) and thus being a novel marker for financial ability, obituaries could also be a useful, innovative data source internationally for historical analyses or "nowcasting" health inequalities.

Analysis of Worldwide Greenhouse and Carbon Monoxide Gas Emissions: Which Countries Exhibit a Special Pattern? A Closer Look via Twitter.

There is significant global concern about the harmful effects of greenhouse gas and carbon monoxide emissions (deforestation, air pollution, global warming, etc.). The 2015 Paris Agreement on climate change aspires to reduce global warming by achieving a climate-neutral world. Research has been carried out to calculate and diminish the aforementioned emissions in waste, power industry, transport, building, in addition to other areas. The aim of this paper is to analyse the carbon and greenhouse gas emissions across countries around the globe in order to find patterns and correlate them to socio-economic indicators [gross national income (GNI), industrial production (IPI) and human development indexes (HDI)] as well as Twitter interactions regarding climate change. For this purpose, time series and socio-economic data have been downloaded from different repositories including EDGAR (Emissions Database for Global Atmospheric Research), World Bank and UNDP (United Nations Development Programme). Although classical clustering algorithms have already been used in the examination of some environmental issues, we use a non-parametric time series clustering method, which has been suggested in certain scientific literature as a more flexible approach, since any ad hoc parametric assumptions are required. The chosen socio-economic indicators have also demonstrated their relevance in pieces of research related to various fields. With respect to Twitter, which is one of the most popular social networks nowadays, significant analysis has also been performed on the basis of capturing citizens' perceptions on a multitude of matters. We found that several countries such as Brazil, India, China, Nigeria, Russia, United States, Spain, Andorra, Greece, and Qatar show differences in carbon and greenhouse gas emissions patterns. Besides, there does not seem to be a correlation between GNI, IPI and HDI as well as the above mentioned emissions ( correlation < 0.16 ) . Regarding Twitter interactions, a dissimilarity in the distribution of hashtags was detected between the aforementioned countries and the rest of the world. This research can help to identify countries in which more governmental measures are needed to reduce the type of emissions analysed in certain industrial sectors. In addition, it points out the topics related to climate change that seem to generate the most debate on Twitter for countries with an unusual pattern. Supplementary Information: The online version contains supplementary material available at 10.1007/s41742-023-00510-4.

Predicting socioeconomic indicators using transfer learning on imagery data: an application in Brazil.

Censuses and other surveys responsible for gathering socioeconomic data are expensive and time consuming. For this reason, in poor and developing countries there often is a long gap between these surveys, which hinders the appropriate formulation of public policies as well as the development of researches. One possible approach to overcome this challenge for some socioeconomic indicators is to use satellite imagery to estimate these variables, although it is not possible to replace demographic census surveys completely due to its territorial coverage, level of disaggregation of information and large set of information. Even though using orbital images properly requires, at least, a basic remote sensing knowledge level, these images have the advantage of being commonly free and easy to access. In this paper, we use daytime and nighttime satellite imagery and apply a transfer learning technique to estimate average income, GDP per capita and a constructed water index at the city level in two Brazilian states, Bahia and Rio Grande do Sul. The transfer learning approach could explain up to 64% of the variation in city-level variables depending on the state and variable. Although data from different countries may be considerably different, results are consistent with the literature and encouraging as it is a first analysis of its kind for Brazil.

Establishment of risk acceptance criteria using Life Quality Index: Application to the Indian context.

The formulation of risk acceptance criteria may be coupled gainfully with a prediction of the of investment required to comply with it, an exercise which can benefit from the application of socioeconomic indicators. The Life Quality Index (LQI) is one such indicator which amalgamates human mortality and wealth creation and places an implicit economic value on reduction of life risk. While there have been a number of studies to demonstrate the application of LQI pertaining to various technological systems, the present work extends it to estimate the sectoral level investment needed to reduce public risks to within the As Low As Reasonably Predictable region for the chemical industry, with specific illustration of the methodology for India. The potential reduction in public individual risk is computed as a function of percentage increase in safety investment expressed as a fraction of the industry's contribution to the nation's GDP. In addition, using a new, more accurate expression, estimates of a related parameter, the implied cost of averting a fatality (ICAF), are obtained for a number of developed economies and India. The ICAF estimates show reasonable agreement with the value of statistical life (VSL), a parameter which is integral to cost-benefit analysis of safety and environmental regulations.

Household air pollution and childhood stunting in China: A prospective cohort study.

Background: Exposure to air pollution, especially indoor air pollution, was associated with an increased risk of childhood stunting. However, few longitudinal studies have explored the long-term impacts of indoor air pollution from household solid fuel use on child growth. We aimed to investigate the association between household air pollution (HAP) from solid fuel use and childhood stunting in Chinese children. Method: The longitudinal data from the Chinese Family Panel Study over 2010-2018 were included in this study with a total of 6,013 children aged 0-15 years enrolled at baseline. Exposure to HAP was measured as solid fuel use for cooking, while solid fuel was defined as coal and firewood/straw according to the questionnaire survey. Stunting was defined as-2SD below the height-for-age z-score (HAZ) of the reference children. Logistic regression and Cox proportional hazards models with time-varying exposures were employed to estimate the association between childhood stunting and HAP exposure. Results: At baseline, children with exposure to HAP from combusting solid fuels had a relatively higher risk of stunting [OR (95%CI): 1.42 (1.24-1.63)]. Among children without stunning at baseline, those living in households with solid fuel use had a higher stunting risk over an 8-year follow-up [HR (95%CI): 2.05 (1.64-2.57)]. The risk of childhood stunting was increased for those with HAP exposure from firewood/straw combustion or with longer exposure duration [HR (95%CI): 2.21 (1.74-2.79) and 3.01 (2.23-4.08), respectively]. Meanwhile, this risk was significantly decreased among children from households switching from solid fuels to clean fuels [HR (95%CI): 0.53 (0.39-0.70)]. Solid fuel use was suggested to be a mediator of the relationship between poor socioeconomic factors (i.e., household income and parental education level) and childhood stunning, with a mediation effect ranging from 11.25 to 14.26%. Conclusions: HAP exposure from solid fuel use was associated with childhood stunting. Poor parental education and low household income might be socioeconomic factors contributing to solid fuel use. Therefore, household energy policies to facilitate access to clean fuels are urgently needed, especially for low-income and low-educated households.

Palm oil-based bioenergy sustainability and policy in Indonesia and Malaysia: A systematic review and future agendas.

This paper reviews previous research on the sustainability and policies of palm oil-based bioenergy in Indonesia and Malaysia. A systematic literature review with a meta-analysis (PRISMA) methodology was performed to evaluate the related articles discussing sustainability and bioenergy policies. This study found 96 articles that mapped the sustainability and policies of bioenergy in Indonesia and Malaysia over the last decade. The sustainability studies were divided into two areas: the environment and socioeconomics. Researchers were more likely to examine environmental factors than socioeconomic factors, specifically focusing on the following environmental indicators: land use conversion, deforestation, and CO2 emissions. Most policy studies concentrated on sustainability and energy security. Over the last two decades, the development of bioenergy policies in Indonesia and Malaysia has been comparable in terms of geographical position and palm oil production. However, Indonesia's bioenergy policy has tended to be more vigorous and dynamic than Malaysia.

Quantitative analysis of the impact of various urban socioeconomic indicators on search-engine-based estimation of COVID-19 prevalence.

Numerous studies have proposed search engine-based estimation of COVID-19 prevalence during the COVID-19 pandemic; however, their estimation models do not consider the impact of various urban socioeconomic indicators (USIs). This study quantitatively analysed the impact of various USIs on search engine-based estimation of COVID-19 prevalence using 15 USIs (including total population, gross regional product (GRP), and population density) from 369 cities in China. The results suggested that 13 USIs affected either the correlation (SC-corr) or time lag (SC-lag) between search engine query volume and new COVID-19 cases ( p <0.05). Total population and GRP impacted SC-corr considerably, with their correlation coefficients r for SC-corr being 0.65 and 0.59, respectively. Total population, GRP per capita, and proportion of the population with a high school diploma or higher had simultaneous positive impacts on SC-corr and SC-lag ( p <0.05); these three indicators explained 37-50% of the total variation in SC-corr and SC-lag. Estimations for different urban agglomerations revealed that the goodness of fit, R 2 , for search engine-based estimation was more than 0.6 only when total urban population, GRP per capita, and proportion of the population with a high school diploma or higher exceeded 11.08 million, 120,700, and 38.13%, respectively. A greater urban size indicated higher accuracy of search engine-based estimation of COVID-19 prevalence. Therefore, the accuracy and time lag for search engine-based estimation of infectious disease prevalence can be improved only when the total urban population, GRP per capita, and proportion of the population with a high school diploma or higher are greater than the aforementioned thresholds.

The magnitude, diversity, and distribution of the economic costs of invasive terrestrial invertebrates worldwide.

Invasive alien species (IAS) are a major driver of global biodiversity loss, hampering conservation efforts and disrupting ecosystem functions and services. While accumulating evidence documented ecological impacts of IAS across major geographic regions, habitat types and taxonomic groups, appraisals for economic costs remained relatively sparse. This has hindered effective cost-benefit analyses that inform expenditure on management interventions to prevent, control, and eradicate IAS. Terrestrial invertebrates are a particularly pervasive and damaging group of invaders, with many species compromising primary economic sectors such as forestry, agriculture and health. The present study provides synthesised quantifications of economic costs caused by invasive terrestrial invertebrates on the global scale and across a range of descriptors, using the InvaCost database. Invasive terrestrial invertebrates cost the global economy US$ 712.44 billion over the investigated period (up to 2020), considering only high-reliability source reports. Overall, costs were not equally distributed geographically, with North America (73%) reporting the greatest costs, with far lower costs reported in Europe (7%), Oceania (6%), Africa (5%), Asia (3%), and South America (< 1%). These costs were mostly due to invasive insects (88%) and mostly resulted from direct resource damages and losses (75%), particularly in agriculture and forestry; relatively little (8%) was invested in management. A minority of monetary costs was directly observed (17%). Economic costs displayed an increasing trend with time, with an average annual cost of US$ 11.40 billion since 1960, but as much as US$ 165.01 billion in 2020, but reporting lags reduced costs in recent years. The massive global economic costs of invasive terrestrial invertebrates require urgent consideration and investment by policymakers and managers, in order to prevent and remediate the economic and ecological impacts of these and other IAS groups.

What do we know about the impact of economic recessions on mortality inequalities? A critical review.

Historically, there has been a debate on the effects of recessions on population health, and especially on mortality and its distribution across different social groups. This paper contributes to this discussion by means of a critical review of the research on the impact of economic recessions on mortality inequalities in the period 1980-2020. We analyzed 19 studies according to their mortality outcomes, socioeconomic indicators, design, analysis, and main findings. Twelve studies focused on European countries or urban areas, two on Asian countries, two on Russia, one on Asia and Europe, one on the USA, and one in Somalia. Five articles included cross-country comparisons (four between European countries or cities and one between Asian and European countries). The Great Recession of 2008 was the most researched economic crisis, followed by country-specific crises in the 90s, the fall of the Soviet Union, and some crises during the 80s. Most studies (n = 15) showed an overall or partial increase in mortality inequalities after an economic recession. However, two papers found a decrease in mortality inequalities due to the worsening of the health of the upper and middle classes, one article found a decrease in inequalities due to a general improvement in population health, and a study found a "slow-down" effect of pre-existent mortality inequalities.

The mathematical relationship between COVID-19 cases and socio-economic indicators of OECD countries.

In most aspects, the COVID-19 pandemic has been the most impactful disease in the last few decades. Although two years have passed since the start of the COVID-19 pandemic, it is clear that the pandemic is far from being brought under full control. This pandemic, which was kept under control in part by the discovery of vaccines, has had a negative impact on people's daily lives as well as global economies. The transmission and death rate of this disease, which was detected in Wuhan, China in December 2019, has differed between countries. The reason for these different rates according to countries has been investigated while developing a mathematical model in this comprehensive study. The effect of 16 different socioeconomic indicators of countries on the parameters of the COVID-19 pandemic was analyzed in this study, which was performed on 35 countries, the majority of which are OECD countries. The main objective of this research is to minimize potential negative effects by improving or taking these indicators into account in future similar outbreaks. In this study, canonical correlation analysis was used to obtain the appropriate mathematical model and the performance of the obtained model has been tested statistically. According to the mathematical model obtained, the age factor comes to the fore as the most important indicator in the COVID-19 pandemic and the next important indicator is the health expenditures of the countries. The influence of 16 different socioeconomic indicators on the COVID-19 pandemic parameters are presented as a percentage with details.

Solid waste generation indicators, per capita, in Amazonian countries.

Countries participating in the Amazon Cooperation Treaty Organization have few options for the environmentally appropriate final disposal of municipal solid waste. Thus, sustainable practices aimed at reducing the negative effects of such a disposal on the environment are complex and hard to accomplish, since solid waste generation per capita proportionally increases as populations grow (≈ 2.7% > world average), mainly in countries inserted in Amazon Cooperation Treaty Organization. Thus, demographic, socioeconomic, management, and ecological factors represented by 18 independent variables were statistically analyzed to explain waste per capita variation in Amazonian countries and sub-regions. Multiple Kruskal-Wallis tests were applied; 13 of them recorded significant results (p < 0.05). Subsequently, simple and multivariate regression analyses were carried out by taking into consideration waste per capita and significant variables. Simple regression results recorded for variables "IAC" and "Gini index" were significant (RIAC2 = 60.09%, RGini2 = 30.83%), with emphasis on "Amazon biome" (DF = 33, p < 0.01, RBiome2 = 5.34%). Multivariate models resulted in wide explainability variation, depending on the number and type of available variable (54.47% ≤ Raj2 ≤ 70.83%), with emphasis on "IAC," "Ptot," "Purb," "Wton," "Lon," Area, "HDI," "Gini," and "SDG11" (p < 0.01). In conclusion, waste per capita estimation models can present variations and geographical interdependencies due to different variables and factors that reflect the current public policies and municipal solid waste management practices.

Vulnerabilidade ao nascer e condicionalidades: estimação com efeitos fixos entre 2012 e 2016 / Vulnerability at birth and conditionalities: estimation with fixed effects between 2012 and 2016 / Vulnerabilidad al nacer y condicionalidades: estimación con efectos fijos entre 2012 y 2016

Resumo O objetivo deste trabalho é analisar a relação da vulnerabilidade ao nascer, representada pela variável baixo peso ao nascer (BPN), com variáveis selecionadas, tais como PIB real per capita e cobertura do Programa Bolsa Família, além de indicadores municipais acerca de características maternas que envolvem idade, número de consultas pré-natais, raça, estado civil e anos de estudo. Estes indicadores foram obtidos a partir de microdados de todos os recém-nascidos provenientes de cada município do território brasileiro, registrados no Sistema de Informações sobre Nascidos Vivos (Sinasc). Os resultados sugerem que as principais causas do BPN para a amostra considerada são o fato de o município possuir um menor PIB real per capita, a maior cobertura do Programa Bolsa Família, a maior proporção de mães com menos de 19 anos e mais de 39 anos e a maior proporção de mães que realizaram até três consultas pré-natais. Conclui-se que políticas públicas que contribuam para o aumento da renda das famílias, estimulem o acompanhamento pré-natal e levem a prevenir a gravidez na adolescência podem contribuir para a redução da ocorrência de peso baixo ao nascer.

Abstract The objective of this paper is to analyze the relationship between vulnerability at birth, represented by the variable low birth weight, and selected variables, such as real GDP per capita and an indicator of the Bolsa Família Program coverage, in addition to municipal indicators about maternal characteristics that involve age, number of prenatal checkups, race, marital status and years of education. These indicators were obtained from microdata of all newborns from each municipality in the Brazilian territory registered in the Information System on Live Births (SINASC). The results found suggest that the main causes of LBW for the sample considered refer to the municipality having a lower real GDP per capita, higher Bolsa Família Program coverage, higher proportion of mothers under 19 and over 39 years old and greater proportion of mothers who had up to three prenatal checkups. It is concluded that public policies that help increase family income, encourage prenatal care and lead to preventing teenage pregnancy can contribute to reducing the incidence of low birth weight.

Resumen El objetivo de este trabajo es analizar la relación entre la vulnerabilidad al nacer, representada por la variable bajo peso al nacer, con variables seleccionadas, tales como producto interno bruto (PIB) real per cápita y un indicador de cobertura del programa Bolsa Familia, además de indicadores municipales acerca de características maternas que implican edad, número de consultas prenatales, etnia-raza, estado civil y años de estudio. Estos indicadores fueron obtenidos a partir de microdatos de todos los recién nacidos provenientes de cada municipio del territorio brasileño registrados en el Sistema de Informaciones sobre Nacidos Vivos (SINASC). Los resultados sugieren que las principales causas del bajo peso al nacer para la muestra considerada implican que el municipio posee un menor PIB real per cápita, mayor cobertura del programa Bolsa Familia, mayor proporción de madres menores de 19 años y mayores de 39 años y mayor proporción de madres que hicieron hasta tres consultas prenatales. Se concluye que políticas públicas que contribuyan al aumento de la renta de las familias, estimulen el acompañamiento prenatal y prevengan el embarazo en la adolescencia pueden contribuir con la reducción de la incidencia de peso bajo al nacer.

Good intentions, unintended outcomes: Impact of social assistance on tobacco consumption in Indonesia.

INTRODUCTION: Social assistance programs create an income effect that allows low-income groups to raise their consumption to improve their well-being. However, this may unintentionally induce an increase in their consumption of temptation goods, including tobacco. By analyzing five massive social assistance programs distributed by the government since 2007, we explore whether those programs may induce increased smoking intensity in Indonesia. METHODS: This study is a quantitative study that applies a Tobit regression, Difference-in-Differences (DiD) regression, Difference regression, and two-sample t-test, using the 2017 Susenas (National Socioeconomic Survey) and the 2007 and 2014 Indonesia Family Life Survey. Estimations using sociodemographic, regional, and social assistance dummy variables are used to explore the impact of the programs on the intensity of cigarette consumption in Indonesia, simultaneously assessing the relationship between cigarette consumption and socioeconomic conditions. RESULTS: Our estimations using Tobit regressions confirm that social assistance recipients consume 3.39 cigarettes per capita per week more than non-recipients. The DiD regressions on IFLS panel data show that social assistance programs significantly increase cigarette consumption by 2.8 cigarettes per capita per week. We also find that: 1) smokers have lower socioeconomic indicators than non-smokers in terms of nutrition and health and education expenditures, and 2) younger household members living with smokers have less educational attainment and higher average sick days. CONCLUSIONS: There is reasonable evidence to support the hypothesis that social assistance programs in Indonesia have contributed to the greater intensity of tobacco consumption among the recipients. The findings call for policy reforms in social assistance programs to be warier with the eligibility conditions for social assistance recipients. Adding new conditions related to smoking behaviors might reduce the smoking intensity of those in low-income groups and, in the long run, might improve the effectiveness of social assistance programs in raising the socioeconomic welfare of the low-income population.

Locating Hotspots for the Social Life Cycle Assessment of Bio-Based Products from Short Rotation Coppice.

The establishment of new value chains raises expectations in economic and social benefits. To determine whether these expectations can be fulfilled or whether there are also negative consequences, social aspects should be assessed as early as the R&D phase. Potential social impacts can be assessed with the help of a social life cycle assessment (SLCA). A common problem in SLCA studies is the large number of social aspects. Thus, it is important to prioritize the most relevant aspects. Scholars agree that socioeconomic indicators should not be selected on a purely intuitive and common sense basis and that a standardized approach is missing. A three-step process has been developed to identify the most vulnerable and relevant social aspects. These three steps were implemented into a case study to empirically test the method. Short-rotation-coppice as an alternative form of agricultural dendromass production is one possibility to obtain wood resources for the processing of bio-based products. The use of agricultural land for dendromass production promises additional income for the region's farmers and job opportunities for the local population. The extant literature shows that the most frequently addressed impacts are related to workers' health and safety aspects. The outcome of this study aims to support future research by identifying an appropriate approach for the selection of indicators in SLCA. For studies with a similar focus, the proposed set of indicators can be used as a framework in itself or serve as a basis for the choice of relevant social indicators. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12155-021-10261-9.

Fecal sterols as sewage contamination indicators in Brazilian mangroves.

Recent sewage contamination in Brazilian mangrove forests was evaluated using fecal sterols as biomarkers and socioeconomic indicators. The sterols were quantified by gas chromatography/mass spectrometry (GC/MS). Total fecal sterol concentrations ranged between 2.50 2.50 and 39.03 µg g-1 and coprostanol, between 0.23 and 6.97 µg g-1. Mangroves located in less urbanized regions presented low coprostanol levels and low coprostanol/cholesterol and (5ß/5ß + 5α) stanol ratios in sediment, while urban mangrove forests presented moderate fecal contamination. In the latter, an intense contribution of untreated domestic effluents associated to metropolitan areas was noted, leading to a significant correlation between coprostanol concentrations and inadequate sanitation, reflecting environmental problems associated to disorderly urbanization processes coupled to the absence of an adequate urban infrastructure. However, even in metropolitan areas, fecal sterol levels did not reach those of highly contaminated regions, probably due to the intense and accelerated degradation process typical of tropical environments. However, this study highlights the importance of fecal contamination assessment in mangrove areas since the presence of untreated sewage in these ecosystems is an issue of public and environmental health.

Association of Selected Area-Level Indicators With Suicide Mortality in Slovenian Municipalities.

Background: With an average suicide rate of 20 per 100,000 in the last decade, Slovenia is above the EU average. There are considerable regional differences in suicide mortality within the country. Aim: We aimed to investigate the relationship between selected indicators at area level and the suicide rate in Slovenian municipalities. Method: Sociodemographic, socioeconomic, and (mental) health data in the years 2012-2016 were analyzed for 212 municipalities. Robust correlation and regression analyses were performed to determine the relationship between different variables and the suicide rate. Results: The suicide rate was positively associated with the percentage of male inhabitants, the high social cohesion in the neighborhood, and the number of sick leave days per capita. It was negatively related to the net income per capita, the marriage rate, the divorce rate, and the availability of professional mental healthcare services. Limitations: The small suicide frequencies within municipalities constitute a limitation of the study. Conclusion: Factors at local, municipal level can be linked to the risk of suicide. In Slovenia, neighborhood cohesion is one of the factors that should be considered when designing suicide prevention measures in a community.