DAS28-γGT for the prediction of major cardiovascular events in rheumatoid arthritis: results from the ESPOIR cohort.

OBJECTIVE: To validate the predictive value of the DAS28 γ-glutamyl transferase (DAS28-γGT) for the occurrence of major cardiovascular (CV) events (MACE) in the 'Etude et Suivi des Polyarthrites Indifférenciées Récentes' ESPOIR cohort. METHODS: Analysis of 13-year outcome from the ESPOIR cohort. RA patients with missing data for baseline γGT activity and those not followed-up to 1 year were excluded. Baseline DAS28-γGT was calculated using the following formula: 0.56*√TJ-28 + 0.28 * √SJ-28 + 2*ln(γGT) + 0.014 * GH. Our primary outcome was the merit of the DAS28-γGT in predicting the occurrence of MACE. RESULTS: Among the 696 patients [536 women, mean (s.d.) age of 49 (12) years], 34 MACE were recorded, with a mean time to event of 71 (44) months. Receiver operating characteristic curve analysis indicated that a DAS28-γGT >9.4 had the best sensitivity and specificity for the diagnosis of MACE during the observation period. DAS28-γGT >9.4 was predictive of the occurrence of MACE, with a hazard ratio (HR) of 3.11 (95% CI 1.41, 5.43). Multivariate Cox analyses confirmed higher DAS28-γGT (HR 2.44, 95% CI 1.05, 5.64) together with age (HR 1.04, 95% CI 1.01, 1.07) and diabetes mellitus (HR 4.12, 95% CI 1.55, 10.95) as independent predictors of MACE. There was a dose effect of the DAS28-γGT for MACE-risk prediction, which was in line with the application of the Framingham risk score. CONCLUSION: The DAS28-γGT was identified in this large prospective cohort as an independent predictor of MACE in patients with RA. The DAS28-γGT is a simple and useful tool to evaluate CV risk in routine and warn the clinician about the CV risk burden in patients with RA.

Anthropometric failures and its predictors among under five children in Ethiopia: multilevel logistic regression model using 2019 Ethiopian demographic and health survey data.

BACKGROUND: Composite Index of Anthropometric Failure (CIAF) combines all three forms of anthropometric failures to assess undernutrition status of children. There is no study on CIAF to identify the real and severe form of under nutrition among Ethiopian children that addressed community level factors. So, this study determined CIAF and identified important factors which helps to design appropriate intervention strategies by using multi-level advanced statistical model. METHODS: The study included 5,530 under five children and utilized a secondary data (EMDHS 2019) which was collected through community-based and cross-sectionally from March 21 to June 28, 2019. Composite index of anthropometric failure among under five children was assessed and a two-stage sampling technique was used to select the study participants. Descriptive summary statistics was computed. A multi-level binary logistic regression model was employed to identify important predictors of CIAF in under five children. Adjusted odds ratio with its 95% CI was estimated and level of significance 0.05 was used to determine significant predictors of CIAF. RESULTS: The prevalence of composite index of anthropometric failure (CIAF) was 40.69% (95% CI: 39.41, 42.00) in Ethiopia. Both individual and community level predictors were identified for CIAF in under five children. Among individual level predictors being male sex, older age, short birth interval, from mothers who have not formal education, and from poor household wealth quintile were associated with higher odds of CIAF among under five children. Low community women literacy and being from agriculturally based regions were the community level predictors that were associated with higher odds of CIAF in under five children in Ethiopia. CONCLUSIONS: The burden of composite index of anthropometric failure in under five children was high in Ethiopia. Age of child, sex of child, preceding birth interval, mother's education, household wealth index, community women literacy and administrative regions of Ethiopia were identified as significant predictors of CIAF. Therefore, emphasis should be given for those factors to decrease the prevalence of CIAF in under five children in Ethiopia.

Measuring social well-being among the older adults: introducing a composite index.

Assessing and monitoring social policies designed to enhance the well-being of older adults necessitates a comprehensive metric that encompasses all facets of their lives. In 2019, a cross-sectional study was carried out in Tehran, Iran, involving interviews with 1 280 older individuals to gauge their well-being. The Older Adults' Social Well-being Index (OSWI) was formulated following the composite indicator construction methodology advocated by the Organization for Economic Co-operation and Development. The study revealed that physical health, living standards, insurance coverage, subjective well-being, and social relationships collectively accounted for 54, 67% of the variation in social well-being. District 22 emerged as the most favorable locale in terms of OSWI, while District 18 lagged behind as the least suitable. The municipal districts of Tehran can be categorized into five distinct groups based on the well-being of their residents. By employing OSWI, the study succinctly encapsulates critical dimensions of older adults' lives, uncovering significant disparities in social well-being across Tehran's districts.

Overall lifestyle changes in adulthood are associated with cancer incidence in the Norwegian Women and Cancer Study (NOWAC) - a prospective cohort study.

BACKGROUND: Cancer is a leading cause of premature death worldwide and incidence is expected to rise in the coming decades. Many cohort studies, measuring lifestyle factors at one time-point, have observed that overall healthy lifestyles were inversely related to cancer incidence. However, there is little knowledge on the impact of lifestyle modification within adulthood. METHODS: Using the Norwegian Women and Cancer study, two repeated self-reported assessments of lifestyle behaviours were used to calculate healthy lifestyle index scores at each time-point (N = 66 233). The associations between change in healthy lifestyle index score and lifestyle-related cancer incidence, including alcohol-, tobacco-, obesity-, and reproductive-related, and site-specific breast and colorectal cancer incidence were estimated using Cox proportional hazard regression models. To assess nonlinearity in the dose-response relationships, restricted cubic spline models were used. RESULTS: Independent of baseline lifestyle, positive lifestyle changes were inversely related to the incidence of overall lifestyle-related cancers, as well as alcohol-related, tobacco-related, obesity-related, and reproductive-related cancers, but not breast and colorectal site-specific cancers. An association between lifestyle worsening and cancer incidence compared to stable lifestyle was observed. CONCLUSIONS: This study provides evidence that overall lifestyle changes among cancer-free women between the ages of 41 and 76 impact the incidence of many cancer types. Regardless of baseline lifestyle, there was a negative dose-response relationship between magnitude of positive lifestyle change and the incidence of overall lifestyle-related cancers. We observed that underlying this trend was an especially clear association between lifestyle worsening and increased risk compared to stable lifestyle. For adult women, maintaining a stable healthy lifestyle and lifestyle improvement are important for preventing the occurrence of many cancer types.

Kernel-Free Quadratic Surface Support Vector Regression with Non-Negative Constraints.

In this paper, a kernel-free quadratic surface support vector regression with non-negative constraints (NQSSVR) is proposed for the regression problem. The task of the NQSSVR is to find a quadratic function as a regression function. By utilizing the quadratic surface kernel-free technique, the model avoids the difficulty of choosing the kernel function and corresponding parameters, and has interpretability to a certain extent. In fact, data may have a priori information that the value of the response variable will increase as the explanatory variable grows in a non-negative interval. Moreover, in order to ensure that the regression function is monotonically increasing on the non-negative interval, the non-negative constraints with respect to the regression coefficients are introduced to construct the optimization problem of NQSSVR. And the regression function obtained by NQSSVR matches this a priori information, which has been proven in the theoretical analysis. In addition, the existence and uniqueness of the solution to the primal problem and dual problem of NQSSVR, and the relationship between them are addressed. Experimental results on two artificial datasets and seven benchmark datasets validate the feasibility and effectiveness of our approach. Finally, the effectiveness of our method is verified by real examples in air quality.

A community-based cross-sectional study to assess the burden of prevalence of undernutrition in 0-6 Years Anganwadi Children of Panvel Block, Raigad District, Maharashtra.

An impaired nutritional status in preschool children leaves significant impact on their overall childhood development. A community-based, cross-sectional study was conducted in Panvel, Maharashtra, over 15 months to assess the overall prevalence and patterns of undernutrition in preschool children using the composite index of anthropometric failure (CIAF). The sample size of 8542 was obtained from randomly selected 132 Anganwadis. Conventional indices (underweight, stunting, and wasting) and CIAF classification were used to assess the prevalence of undernutrition. Statistical analysis was performed using the SPSS version 27. About 50.6% of children were detected as "anthropometric failure" by CIAF method which is higher than conventional indices for underweight (32.9%), stunting (35.7%), and wasting (16.4%). The 13-25 months' age group was most significantly affected (57%) as per the CIAF. Undernutrition prevalence was similar for both genders across all age groups. A comprehensive policy is needed to identify and treat all anthropometrical failure children with special emphasis on 13-25 months' age group.

Measurement and mapping of maternal health service coverage through a novel composite index: a sub-national level analysis in India.

BACKGROUND: Expansion of maternal health service coverage is crucial for the survival and wellbeing of both mother and child. To date, limited literature exists on the measurement of maternal health service coverage at the sub-national level in India. The prime objectives of the study were to comprehensively measure the maternal health service coverage by generating a composite index, map India by categorizing it into low, medium and high zones and examine its incremental changes over time. METHODS: Utilising a nationally representative time series data of 15 key indicators spread across three domains of antenatal care, intranatal care and postnatal care, we constructed a novel 'Maternal Health Service Coverage Index' (MHSI) for 29 states and 5 union territories of India for the base (2017-18) and reference (2019-20) years. Following a rigorous procedure, MHSI scores were generated using both arithmetic mean and geometric mean approaches. We categorized India into low, medium and high maternal health service coverage zones and further generated geospatial maps to examine the extent and transition of maternal health service coverage from base to reference year. RESULTS: India registered the highest mean percentage coverage (93.7%) for 'institutional delivery' and the lowest for 'treatment for obstetric complications' (9.3%) among all the indicators. Depending on the usage of arithmetic mean and geometric mean approaches, the maternal health service coverage index score for India exhibited marginal incremental change (between 0.015-0.019 index points) in the reference year. West zone exhibited an upward transition in the coverage of maternal health service indicators, while none of the zones recorded a downward movement. The states of Mizoram (east zone) and the Union Territory of Puducherry (south zone) showed a downward transition. Union territories of Dadra & Nagar Haveli (west zone) and Chandigarh (north zone), along with the states of Maharashtra (west zone), Assam, as well as Jharkhand (both from the east & north east zone), showed upward transition. CONCLUSION: Overall, maternal health service coverage is increasing across India. Our study offers a novel summary measure to comprehensively quantify the coverage of maternal health services, which can momentously help India identify lagged indicators and low performing regions, thereby warranting the targeted interventions and concentrated programmatic efforts to bolster the maternal health service coverage at the sub-national level.

Sensitivity of environmental performance index based on stochastic dominance.

The Environmental Performance Index (EPI) is a popular sustainability index. It is a composite index which ranks 180 countries based on their environmental performance in 32 indicators. Using the EPI data and stochastic dominance efficiency methodology, this paper examines the sensitivity to the subjective weights assigned to the indicators and categories of environmental performance. The findings show a remarkable variation in environmental performance based on alternative weights which are selected using Stochastic Dominance criteria. Except for 2020, the environmental health category in EPI gets relatively higher importance in the optimal scenario, and ecosystem vitality gets relatively higher weights in the inferior scenario, suggesting that the environmental health category achievements have been relatively higher for most countries over time. The ranking analysis also shows major variations in country rankings with alternative weights. Two countries, Maldives and Gabon, would have experienced more than 100 position changes in their rankings with alternative weights. Furthermore, 67 countries would have experienced 30 or more position changes in their rankings and 37 countries experienced an EPI score change of more than 50 (out of 100) with alternative weights. Overall, the results illustrate the importance of sensitivity analysis of composite indices to increase reliability and transparency.

Antioxidant Capacity of Herzegovinian Wildflowers Evaluated by UV-VIS and Cyclic Voltammetry Analysis.

Considering the vast cultural and traditional heritage of the use of aromatic herbs and wildflowers for the treatment of light medical conditions in the Balkans, a comparison of the antioxidant capacity of wildflowers extracts from Herzegovina was studied using both cyclic voltammetry and spectrophotometry. The cyclic voltammograms taken in the potential range between 0 V and 800 mV and scan rate of 100 mV s-1 were used for the quantification of the electrochemical properties of polyphenols present in four aqueous plant extracts. Antioxidant capacity expressed as mmoL of gallic acid equivalents per gram of dried weight of the sample (mmoL GAE g-1 dw) was deduced from the area below the major anodic peaks (Q400 pH 6.0, Q500 pH 4.7, Q600 pH 3.6). The results of electrochemical measurements suggest that the major contributors of antioxidant properties of examined plants are polyphenolic compounds that contain ortho-dihydroxy-phenol or gallate groups. Using Ferric reducing-antioxidant power (FRAP) and 2,2'-azino-bis spectrophotometric methods (3-ethylbenzthiazoline-6-sulphonic acid) radical cation-scavenging activity (ABTS) additionally determined antioxidant capacity. The FRAP results ranged from 2.9702-9.9418 mmoL Fe/g dw, while the results for ABTS assays expressed as Trolox equivalents (TE) ranged from 14.1842-42.6217 mmoL TE/g dw. The Folin-Ciocalteu procedure was applied to determine the total phenolics content (TP). The TP content expressed as Gallic acid equivalents (GAE) ranged from 6.0343-9.472 mmoL GAE/g dw. The measurements of total flavonoid (TF) and total condensed tannin (TT) contents were also performed to obtain a broader polyphenolic profile of tested plant materials. Origanum vulgare L. scored the highest on each test, with the exception of TT content, followed by the Mentha × piperita L., Artemisia annua L., and Artemisia absinthium L., respectively. The highest TT content, expressed as mg of (-)catechin equivalents per gram of dried weight of sample (mg CE/g dw), was achieved with A. absinthium extract (119.230 mg CE/g dw) followed by O. vulgare (90.384 mg CE/g dw), A. annua (86.538 mg CE/g dw) and M. piperita (69.231 mg CE/g dw), respectively. In addition, a very good correlation between electrochemical and spectroscopic methods was achieved.

Environmental energy security in the MENA region - an aggregated composite index.

Energy security is a multi-dimensional concept that is gaining a growing interest worldwide for studying the sustainability of a given energy sector. The level of energy security has been always quantified and evaluated by focusing on economic and technical dimensions, and modest importance was attributed to social and environmental aspects. Moreover, countries of the Middle East and North Africa (MENA) region were always under-reported in the literature pertaining to energy security issues. This study strives to evaluate energy security in this region through the establishment of an original Environmental Energy Security Index (EESI) in order to cover different dimensions of security of energy supply within these counties. A total of nine sub-indicators were selected based on the current policies and orientations in the region. These indicators were normalized, weighted, and aggregated for each country of the MENA region between 2008 and 2017. According to the assessment objectives, results showed that on average Yemen holds the highest EESI score of 5.319 followed by Morocco 4.304 and Algeria 4.087. On the other hands, Bahrain is ranked last 1.610 preceded by UAE 2.249 and Qatar 2.461. Some key proposals were suggested including investment in local resources, diversification of the energy mix, reduction of energy imports, and use of energy-efficient technologies.

Air quality improvement assessment and exposure risk of Shandong Province in China during 2014 to 2020.

As one of the most polluted provinces in China, air pollution events occur frequently in Shandong. Based on the hourly (or daily) concentrations of six air pollutants (PM2.5, PM10, O3, NO2, SO2 and CO), the situations of air quality improvement in three kinds of cities (key cities, coastal cities and general cities) are assessed comprehensively during 2014-2020. Contrary to the daily maximum 8-h average ozone (MDA8 O3), the annual average concentrations of other pollutants show the downward trends during 2014-2020. Therein, the improvement rates of annual average concentrations of air pollutants in key cities are highest. By 2020, the day proportions of O3 as the primary pollutant are up to 38% in three kinds of cities. Besides, due to the impact of COVID-19, the monthly average concentrations of PM2.5, PM10, NO2, SO2 and CO in February 2020 decrease by 32.1-49.5% year-on-year. There are still about 50% of population exposed to high-risk regions (R i > 2), which are mainly concentrated in main urban areas and industrial areas. Thus, the adjustment of industrial structure and energy composition in the context of carbon peak and carbon neutrality should be implemented in the future. Supplementary Information: The online version contains supplementary material available at 10.1007/s13762-022-04651-5.

Transitioning Economic Statuses of Appalachian Counties during COVID-19.

In the past decade, the Appalachian economy in the United States was scarcely discussed in the literature. No studies were devoted to local economic development after the outbreak of the Coronavirus Disease in 2019. This paper fills the literature gap by empirically examining how the Appalachian economy transitioned under the influence of the pandemic. Using county-level data from the Appalachian Regional Commission between 2019 and 2022, the study investigates how the Appalachian economy regressed during the pandemic. Transitioning economy indices were calculated for 420 local counties by comparing their composite index values before and after the outbreak of the pandemic. Regressions were run to estimate the influences of the unemployment rate, per capita income, and the poverty rate. During the pandemic, the unemployment rate consistently had the largest impact on the Appalachian counties' composite index value and the least effect on the poverty rate. The results suggest that the most effective strategy is for the government to reduce the local unemployment rate to improve the economic ranking. Supplementary Information: The online version contains supplementary material available at 10.1007/s11293-022-09749-2.

Spatial data analysis of malnutrition among children under-five years in Ethiopia.

BACKGROUND: Childhood malnutrition is a major cause of child mortality under the age of 5 in the sub-Saharan Africa region. This study sought to identify the risk factors and spatial distribution of the composite index of anthropometric failure (CIAF). METHODS: Secondary data from 2000, 2005, 2011, and 2016 Ethiopian Health and Demographic Survey (EDHS) were used. The generalized geo-additive mixed model was adopted via the Integrated Nested Laplace Approximation (INLA) with a binomial family and logit link function. RESULTS: The CIAF status of children was found to be positively associated with the male gender, the potency of contracting a disease, and multiple births. However, it was negatively associated with family wealth quartiles, parental level of education, place of residence, unemployment status of mothers, improved sanitation, media exposure, and survey years. Moreover, the study revealed significant spatial variations on the level of CIAF among administrative zones. CONCLUSIONS: The generalized geo-additive mixed-effects model results identified gender of the child, presence of comorbidity, size of child at birth, dietary diversity, birth type, place of residence, age of the child, parental level of education, wealth index, sanitation facilities, and media exposure as main drivers of CIAF. The results would help decision-makers to develop and carry out target-oriented programs.

Geographical distribution of risk factors for invasive non-typhoidal Salmonella at the subnational boundary level in sub-Saharan Africa.

BACKGROUND: Invasive non-typhoidal Salmonella (iNTS) is a growing health-concern in many parts of sub-Saharan Africa. iNTS is associated with fatal diseases such as HIV and malaria. Despite high case fatality rates, the disease has not been given much attention. The limited number of population-based surveillance studies hampers accurate estimation of global disease burden. Given the lack of available evidence on the disease, it is critical to identify high risk areas for future surveillance and to improve our understanding of iNTS endemicity. METHODS: Considering that population-based surveillance data were sparse, a composite index called the iNTS risk factor (iNRF) index was constructed based on risk factors that commonly exist across countries. Four risk factors associated with the prevalence of iNTS were considered: malaria, HIV, malnutrition, and safe water. The iNRF index was first generated based on the four risk factors which were collected within a 50 km radius of existing surveillance sites. Pearson product-moment correlation was used to test statistical associations between the iNRF index and the prevalence of iNTS observed in the surveillance sites. The index was then further estimated at the subnational boundary level across selected countries and used to identify high risk areas for iNTS. RESULTS: While the iNRF index in some countries was generally low (i.e. Rwanda) or high (i.e. Cote d'Ivoire), the risk-level of iNTS was variable not only by country but also within a country. At the provincial-level, the highest risk area was identified in Maniema, the Democratic Republic of Congo, whereas Dakar in Senegal was at the lowest risk. CONCLUSIONS: The iNRF index can be a useful tool to understand the geographically varying risk-level of iNTS. Given that conducting a population-based surveillance study requires extensive human and financial resources, identifying high risk areas for iNTS prior to a study implementation can facilitate an appropriate site-selection process in the future.

Health indices for the evaluation and monitoring of health in children and adolescents in prevention and health promotion: a scoping review.

BACKGROUND: Health indicators are used in different settings to monitor health outcomes. Child and adolescent health is arguably one of the most important areas for the application of indices and indicators in prevention and health promotion. Although single health indicators may be better suited to display the complexity of the health status and its determinants, a selected set of indicators will still offer a complex picture. Therefore, it is argued that a group of indicators combined into an index may offer a pragmatic tool that is easier to use in order to inform stakeholders. METHODS: A scoping review was conducted to identify and describe health indices that monitor and evaluate health of children and adolescents and to appraise the quality and value of the identified indices that may guide the further applications of these indices in particular settings. The three bibliographic databases MEDLINE, EMBASE and PsycINFO were searched and a double screening of titles and abstracts as well as double screening of full texts was performed. Indices contained in these studies were analysed in terms of focus and composition and evaluated in terms of quality criteria. RESULTS: The scoping review identified 36 eligible studies with 18 health indices in six thematic categories. Of the identified indices, seven indices focus on anthropometrical variables, three indices focus on special aspects of newborns and five indices focus on oral health. One index assesses "healthy lifestyle" and one "functional ability" whereas one index a combination of different aspects. Most indices are calculated by using primary health data. CONCLUSIONS: Alone or in combination with single sets of indicators, indices in six major thematic domains may be used as pragmatic tools for monitoring children's and adolescents´ health and the evaluation of interventions in health promotion and prevention settings.

Bivariate binary analysis on composite index of anthropometric failure of under-five children and household wealth-index.

BACKGROUND: Malnutrition is the most common cause of mortality and morbidity of children in low and middle income countries including Ethiopia and household wealth index shares the highest contribution. Thus, in this study it is aimed to conduct bivariate binary logistic regression analysis by accounting the possible dependency of child composite index anthropometric failure and household wealth index. METHODS: In this study the data from Ethiopian Demographic and Health Survey (EDHS) 2016 involved 9411 under five children was considered. Child Composite Index Anthropometric Failure (CIAF) measures the aggregate child undernourished derived from the conventional anthropometric indices (stunting, underweight and wasting). The correlation between CIAF and wealth index was checked and significant correlation found. To address the dependency between the two outcome variables bivariate binary logistic regression was used to analyze the determinants of child CAIF and household wealth index jointly. RESULTS: Study results show that region, place of residence, religion, education level of women and husband/partner, sex of child, source of drinking water, household size and number of under five children in the household, mothers body mass index, multiple birth and anemia level of child had significant association with child CIAF. Female children were 0.82 times less likely to be CIAF compared to male and multiple birth children were more likely to be CIAF compared to single birth. Children from Oromia, Somalie, Gambela, SNNPR, Harari and Addis Ababa region were 0.6, 0.56, 0.67, 0.52, 0.6 and 0.44 times less likely to be CIAF compared to Tigray. A household from rural area were 15.49 times more likely poor compared to a household. The estimated odds of children whose mothers attended primary, and secondary and higher education was 0.82, and 0.52 times respectively the estimated odds of children from mothers who had never attended formal education. CONCLUSION: The prevalence of children with composite index anthropometric failure was high and closely tied with the household wealth index. Among the determinants, region, religion, family education level, and anemia level of child were statistically significant determinants of both CIAF and household wealth index. Thus, the authors recommend to concerned bodies and policymakers work on household wealth index to reduce the prevalence of child composite anthropometric failure.

A machine learning classifier approach for identifying the determinants of under-five child undernutrition in Ethiopian administrative zones.

BACKGROUND: Undernutrition is the main cause of child death in developing countries. This paper aimed to explore the efficacy of machine learning (ML) approaches in predicting under-five undernutrition in Ethiopian administrative zones and to identify the most important predictors. METHOD: The study employed ML techniques using retrospective cross-sectional survey data from Ethiopia, a national-representative data collected in the year (2000, 2005, 2011, and 2016). We explored six commonly used ML algorithms; Logistic regression, Least Absolute Shrinkage and Selection Operator (L-1 regularization logistic regression), L-2 regularization (Ridge), Elastic net, neural network, and random forest (RF). Sensitivity, specificity, accuracy, and area under the curve were used to evaluate the performance of those models. RESULTS: Based on different performance evaluations, the RF algorithm was selected as the best ML model. In the order of importance; urban-rural settlement, literacy rate of parents, and place of residence were the major determinants of disparities of nutritional status for under-five children among Ethiopian administrative zones. CONCLUSION: Our results showed that the considered machine learning classification algorithms can effectively predict the under-five undernutrition status in Ethiopian administrative zones. Persistent under-five undernutrition status was found in the northern part of Ethiopia. The identification of such high-risk zones could provide useful information to decision-makers trying to reduce child undernutrition.

Fontan-associated liver disease and total cavopulmonary anatomical flow effectors.

OBJECTIVE: We investigated a relationship between a composite index comprised of Fontan-circuit anatomical features and hepatic fibrosis scores from biopsy. METHODS: We identified living extracardiac Fontan patients, ≥7 years old and ≥5 but <20 years postoperative, that underwent cardiac catheterization and transvenous liver biopsy between March 2012 and September 2020. We divided patients into anatomical groups and applied a risk score to each patient. We compared average anatomical risk scores with average hepatic total fibrosis scores by group. RESULTS: We identified 111 patients that met inclusion criteria. After excluding four patients, we assigned 107 to one of 12 anatomical variant groups (n ≥ 3). For the 107, the average age at liver biopsy was 14 ± 6 years old. Of the 107, 105 (98%) were New York Heart Association Class 1. We found average anatomical risk scores by group correlated with average total fibrosis scores by group (R = 0.8; p = .005). An average Fontan duration to biopsy of 10 ± 1 years was similar for all 12 anatomical groups. We found no other clinical variables, laboratory, or hemodynamic values that trended with anatomical risk scores or hepatic total fibrosis scores. CONCLUSIONS: In a cohort of relatively young, stable extracardiac Fontan patients, average composite anatomical risk scores strongly correlated with average hepatic total fibrosis scores by anatomical group. These findings suggest that some anatomical variants in extracardiac Fontan patients are associated with higher Fontan-associated liver disease (FALD)-related hepatic total fibrosis scores than others, despite similar Fontan durations.

Which region and which sector leads the circular economy? CEBIX, a multivariant index based on business actions.

The circular economy encompasses a sustainable economic model based on a production, consumption, distribution and maintenance process that reuses as much as possible. In this research, the two-step composite Circular Economy Business Index was created, based on 17 environmental practices that companies have implemented to reduce the generation of waste and emissions and to increase the reuse and efficiency of materials and energy, among other actions. The use of a sample of 26,783 companies from 49 countries and 10 sectors for the period 2014-2019 allowed the aggregation of these initiatives at the country and industry levels. In this sense, our results show less progress in the circular transformation worldwide and can be used in the design of policies aimed at promoting changes in production and consumption systems in specific geographic or industrial contexts.

Assessing inequalities and regional disparities in child nutrition outcomes in India using MANUSH - a more sensitive yardstick.

BACKGROUND: India is strongly committed to reducing the burden of child malnutrition, which has remained a persistent concern. Findings from recent surveys indicate co-existence of child undernutrition, micronutrient deficiency and overweight/obesity, i.e. the triple burden of malnutrition among children below 5 years. While considerable efforts are being made to address this challenge, and several composite indices are being explored to inform policy actions, the methodology used for creating such indices, i.e., linear averaging, has its limitations. Briefly put, it could mask the uneven improvement across different indicators by discounting the 'lagging' indicators, and hence not incentivising a balanced improvement. Signifying negative implications on policy discourse for improved nutrition. To address this gap, we attempt to develop a composite index for estimating the triple burden of malnutrition in India, using a more sensitive measure, MANUSH. METHODOLOGY: Data from publicly available nation-wide surveys - National Family Health Survey (NFHS) and Comprehensive National Nutrition Survey (CNNS), was used for this study. First, we addressed the robustness of MANUSH method of composite indexing over conventional aggregation methods. Second, using MANUSH scores, we assessed the triple burden of malnutrition at the subnational level over different periods NHFS- 3(2005-06), NFHS-4 (2015-16) and CNNS (2106-18). Using mapping and spatial analysis tools, we assessed neighbourhood dependency and formation of clusters, within and across states. RESULT: MANUSH method scores over other aggregation measures that use linear aggregation or geometric mean. It does so by fulfilling additional conditions of Shortfall and Hiatus Sensitivity, implicitly penalising cases where the improvement in worst-off dimension is lesser than the improvement in best-off dimension, or where, even with an overall improvement in the composite index, the gap between different dimensions does not reduce. MANUSH scores helped in revealing the gaps in the improvement of nutrition outcomes among different indicators and, the rising inequalities within and across states and districts in India. Significant clusters (p < 0.05) of high burden and low burden districts were found, revealing geographical heterogeneities and sharp regional disparities. A MANUSH based index is useful in context-specific planning and prioritising different interventions, an approach advocated by the newly launched National Nutrition Mission in India. CONCLUSION: MANUSH based index emphasises balanced development in nutritional outcomes and is hence relevant for diverse and unevenly developing economy like India.