Marginal Effect Research Articles

How ‘Inclusion’ Scales: From Marginal Effects to Systems Analysis in the Practice of Development

How ‘Inclusion’ Scales: From Marginal Effects to Systems Analysis in the Practice of Development

Impact of suppliers' risk aversions on information sharing in a hybrid E‐commerce supply chain

AbstractIn practice, suppliers sell their products through online intermediaries who sell them to customers (reselling) or directly access customers via intermediaries by paying a proportional fee (agency selling). Unlike giant intermediaries, these suppliers have smaller scales and are more risk‐averse. Motivated by practical examples, this paper studies these intermediaries' incentives for vertical demand information sharing with their suppliers. We develop a game‐theoretic model to consider a hybrid e‐commerce supply chain with a risk‐neutral intermediary and two risk‐averse suppliers, where one supplier (agency supplier) adopts agency selling while the other supplier (reselling supplier) employs reselling. As a benchmark, we show that it is beneficial for the intermediary to share all (no) information with both risk‐neutral suppliers if the proportional fee is relatively high (low). However, we find that suppliers' risk aversion is a key factor leading to supply chain members' pricing decisions being influenced by the precision of the demand information. This influence impacts the double marginalization effect and further changes the intermediary's information‐sharing decisions. Specifically, the intermediary should disclose part rather than all of its information to both risk‐averse suppliers if the proportional fee is high (intermediate) in a weakly (highly) competitive market environment. Finally, when the reselling supplier's sensitivity to risk is sufficiently high (low) relative to the agency supplier's sensitivity to risk, we observe that the intermediary is less (more) willing to share information.

A Fair Contribution Measurement Method for Federated Learning.

Federated learning is an effective approach for preserving data privacy and security, enabling machine learning to occur in a distributed environment and promoting its development. However, an urgent problem that needs to be addressed is how to encourage active client participation in federated learning. The Shapley value, a classical concept in cooperative game theory, has been utilized for data valuation in machine learning services. Nevertheless, existing numerical evaluation schemes based on the Shapley value are impractical, as they necessitate additional model training, leading to increased communication overhead. Moreover, participants' data may exhibit Non-IID characteristics, posing a significant challenge to evaluating participant contributions. Non-IID data have greatly affected the accuracy of the global model, weakened the marginal effect of the participants, and led to the underestimated contribution measurement results of the participants. Current work often overlooks the impact of heterogeneity on model aggregation. This paper presents a fair federated learning contribution measurement scheme that addresses the need for additional model computations. By introducing a novel aggregation weight, it enhances the accuracy of the contribution measurement. Experiments on the MNIST and Fashion MNIST dataset show that the proposed method can accurately compute the contributions of participants. Compared to existing baseline algorithms, the model accuracy is significantly improved, with a similar time cost.

Assessing marginal effects of non-pharmaceutical interventions on the transmission of SARS-CoV-2 across Africa: a hybrid modeling study.

Since 2019, a new strain of coronavirus has challenged global health systems. Due its fragile healthcare systems, Africa was predicted to be the most affected continent. However, past experiences of African countries with epidemics and other factors, including actions taken by governments, have contributed to reducing the spread of SARS-CoV-2. This study aims to assess the marginal impact of non-pharmaceutical interventions in fifteen African countries during the pre-vaccination period. To describe the transmission dynamics and control of SARS-CoV-2 spread, an extended time-dependent SEIR model was used. The transmission rate of each infectious stage was obtained using a logistic model with NPI intensity as a covariate. The results revealed that the effects of NPIs varied between countries. Overall, restrictive measures related to assembly had, in most countries, the largest reducing effects on the pre-symptomatic and mild transmission, while the transmission by severe individuals is influenced by privacy measures (more than $10\%$). Countries should develop efficient alternatives to assembly restrictions to preserve the economic sector. This involves e.g. training in digital tools and strengthening digital infrastructures.

Determinants of childhood anaemia in India from 2005 to 2021: insights from the last three rounds of India National Family Health Surveys

Anaemia is a global public health problem affecting 800 million women and children globally. Anaemia is associated with perinatal mortality, child morbidity and mortality, mental development, immune competence, susceptibility to lead poisoning, and performance at work. This paper used data from India National Family Health Surveys (INFHS) carried out in 2005-06, 2015-16 and 2019-21 to identify the factors associated with childhood anaemia among children, adjusting for a range of covariates. In NFHS rounds of 3 and 4 after adjusting for standard covariates, in the probit model, it was found according to marginal effects, the probability of children being anaemic in urban areas is lower. Those belonging to the scheduled tribes have a higher probability of being anaemic in the two survey rounds of NFHS-3 and NFHS-4. Literate mothers were found to have a lower probability of anaemia in their children. In NFHS-5, in the binary logit model after adjusting for standard covariates, it was found that those belonging to the scheduled tribes were 1.348 times more likely to be anaemic compared to the scheduled castes. Maternal education was another significant factor determining the likelihood of being anaemic. Literate mothers were less likely to have anaemic children. This study provides crucial insights into the dynamic nature of childhood anaemia in India, utilizing data from three decades of NFHS surveys. It highlights the need for comprehensive interventions addressing socio-economic determinants, education of women, and behaviour change interventions to mitigate the burden of childhood anaemia in India.

Analyzing the Suitability of Vehicle Telematics Data as a Surrogate Safety Measure for Short-Term Crashes

Traffic safety analysis relies heavily on the comprehensiveness of traffic crash data. However, crash occurrences are rare events. Researchers have sought alternative measures closely linked to crash occurrences, known as surrogate safety measures, to address this challenge. The advent of vehicle telematics has introduced a valuable source of data, consisting of time-stamped positional information of vehicles, facilitated through telecommunication networks. Wejo Data Services Inc. collects vehicle telematics data through collaboration with various automotive original equipment manufacturers (OEMs) to furnish connected vehicle data along with driver event variables, such as braking and acceleration. This study seeks to investigate the relationship between hard-braking events and the incidence of total crashes and peak period crashes across different facility types using analysis of variance and negative binomial models. The results show a strong correlation between hard braking and crash frequency. The ratio of hard-braking events to crashes exhibits notable variations across peak hours, off-peak periods, and nighttime. Further, the coefficient of hard braking is significantly higher on freeways compared with non-freeways. The model performance of different short period models improved better than the extent of improvement in total crash model after hard braking was introduced as an explanatory variable. The marginal effects of hard braking on crash frequency on freeways are consistently higher than those in non-freeway segments.

Investigation of the performance of a newly designed solar chimney for enhancing natural ventilation and mitigation of summer overheating

The significant challenge encountered in utilizing Trombe walls for winter heating is summer overheating, which limits the overall feasibility of the system. In response to this issue, the present study introduces a novel model of a Trombe wall-solar chimney system designed to enhance natural ventilation and address the problem of summer overheating. To assess the performance of the proposed model, a full-scale experimental test rig is constructed in Kirkuk, Iraq. This rig comprises a test room integrated with a Trombe wall-solar chimney system. Additionally, a numerical simulation based on the CFD approach along with a computer code is developed to investigate the behavior of the system. System analysis is conducted for the period August 14th–15th. The parameters studied include chimney height (ranging from 0.0m to 2.0m in 0.5m increments), chimney width (0.2m, 0.3m, 0.4m, and 0.5m), room inlet vent height (ranging from 0.2m to 0.4m with 0.05m increments), and chimney inlet vent height (ranging from 0.2m to 0.4m with 0.05m increments). The results highlight the crucial role of the massive storage wall in sustaining nighttime ventilation in the absence of solar energy by utilizing stored heat to warm the air and maintain the ventilation process. The study establishes that chimney height and width significantly influence airflow rate, while other factors have marginal effects. An empirical equation is formulated to predict the 24-h averaged air changes per hour (ACH), which is a critical measure of system performance in ventilation. This equation is developed using artificial neural network (ANN) techniques. Finally, the findings indicate that the suggested model effectively reduces summertime overheating while generating a satisfactory ventilation rate. This enhances the overall versatility and year-round usability of Trombe wall systems, making them more adaptive and efficient in regions with diverse climatic conditions.

Exploring the relationship between condition severity and health-related quality of life in people with haemophilia A across Europe: a multivariable analysis of data from the CHESS II study

BackgroundHaemophilia A (HA; Factor VIII deficiency) is a congenital X-linked bleeding disorder characterized by trauma-related or spontaneous bleeding events, most notably arising within the intraarticular space and resulting in chronic inflammation and degeneration of affected joints. Endogenous clotting factor activity relative to normal levels determines the severity of HA symptoms, as mild (> 5–40%), moderate (1–5%), or severe (< 1%). Within the current environment of rapid evolution in HA management, we seek to understand the interplay of condition severity and health-related quality of life (HRQoL) to characterise and differentiate unmet needs among people with HA (PwHA).MethodsA generalised linear regression model (GLM) was developed to explore the relationship between HA severity and EQ-5D-5 L index score from adult HA patients sampled in the “Cost of Haemophilia across Europe – a Socioeconomic Survey II” (CHESS II) cross-sectional, retrospective burden of illness study among adults with hereditary haemophilia A or B from eight European countries. HA patients of any severity with no active inhibitors during the 12 months prior to data capture and a completeEQ-5D-5 L response were included. A base GLM model was specified with covariates for demographic and clinical characteristics (age, body mass index, country, employment, HA severity, annual bleeding rate, problem joints, and chronic pain).ResultsOf 381 evaluable patients, 221 (58.0%) had severe HA, 96 (25.2%) had moderate HA, and 64 (16.8%) had mild HA. Among the covariates included in the GLM model and after controlling for haemophilia-related outcomes, a significant association was observed between mild HA and higher EQ-5D-5 L index score (average marginal effects, 0.084; p = 0.016) relative to severe HA. Patient country of residence and magnitude of HA-related chronic pain were also associated with significant differences in index scores, with the latter showing a negative relationship with HRQoL outcomes.ConclusionsCondition severity and chronic pain are significant predictors of HRQoL in PwHA. Durable bleeding protection and effective management of chronic pain have the potential to address unmet treatment needs in this population.

Impact of a regulatory target and external factors on the waste efficiency of Italian municipalities.

Due to increasing consumption and urbanisation, urban waste management and recycling are a primary concern in Italy. Italian waste collection underwent significant reform with the introduction of a sorted collection target of 65% of total collected waste in Legislative Decree No. 152/2006. In this article, we analyse the effect of this regulatory target on the efficiency of waste collection in 275 Italian municipalities in the years 2016-2019. We estimate the coefficients of the cost efficiencies of the sorted and unsorted waste without assuming functional forms for the efficient frontier or the distribution of efficiency. Our findings suggest that municipalities that met the 65% sorted waste target demonstrated higher efficiency as costs increased, whereas those that failed to meet the target demonstrated higher inefficiency as costs increased. Strong effects emerged for population and urban economic development on the success of waste collection, whereas only marginal effects were observed for population density and city size. To improve the situation of municipalities that are not meeting the 65% target, we propose several policy measures, including 'neighbourhood solidarity'.

The Effect of Net Interest Margin (NIM), Operating Expenses, Operating Income (BOPO), Loan to Deposit Ratio (LDR), on Return on Assets (ROA) at PT Bank Mayapada Internasional Tbk for the Period of 2014-2023

The Effect of Net Interest Margin (NIM), Operating Expenses, Operating Income (BOPO), Loan to Deposit Ratio (LDR), on Return on Assets (ROA) at PT Bank Mayapada Internasional Tbk for the Period of 2014-2023

Incident Psychotropic Medication Use Among US Commercially Insured Children and Adolescents from 2019 to 2022.

Objective: To compare the proportion of children and adolescents with incident psychotropic medication use from 2019 through 2022. Methods: This cross-sectional study used the IQVIA PharMetrics® Plus for Academics health plan claims database. Our study sample consisted of children and adolescents ages 6-18 who had at least one psychotropic medication in March 2019-February 2022. We examined psychotropic medication use in three distinct study periods: pre-pandemic (March 2019 to February 2020), pandemic-year-1 (March 2020-February 2021), and pandemic-year-2 (March 2021-February 2022). Incident use was defined as no evidence of psychotropic medication in the 12 months preceding the child and adolescent's first psychotropic dispensing in each study period. We estimated incident psychotropic use in the three study periods. Average marginal effects tested for significant differences in psychotropic initiation, overall and stratified by age and sex. Results: In our sample of 42,346 children and adolescents who were dispensed any psychotropic medication during the study period, incident psychotropic users were 27.8% in pre-pandemic, 26.0% in pandemic-year-1, and 27.8% in pandemic-year-2. Incident use of antidepressants was 51.4% in pandemic-year-1 and 54.6% in pandemic-year-2. The probability of incident psychotropic use was 2.4% lower in pandemic-year-1 than in the pre-pandemic year (p < 0.001). The proportion of 6-11-year-olds and females initiating a psychotropic was higher in pandemic-year-2 than pre-pandemic. Conclusion: Incident psychotropic use was most notable in younger and female children 2 years after the pandemic onset.

How can rural digitalization improve agricultural green total factor productivity: Empirical evidence from counties in China

Against the backdrop of escalating environmental pollution and resource depletion induced by traditional agricultural industry development, the imperative for agricultural efficiency and ecologically friendly practices has become pivotal for global agricultural sustainability. In the digital era, rural digitalization has substantially amplified agricultural production efficiency while notably reducing environmental pollution. This study is based on panel data from 1602 counties in China spanning from 2011 to 2020, measuring the levels of rural digitalization and agricultural green total factor productivity (AGTFP) across these counties, empirically examining their dynamic correlation. The research findings reveal: (1) A significant enhancement of AGTFP with the elevation of rural digitalization; for every 1 % increase in rural digitalization, AGTFP increases by 1.78 %. Robustness checks, including instrumental variables and quasi-natural experiments, affirm the validity of these conclusions. Furthermore, by comparing regional differences in China, it can be observed that the impact of rural digitalization on AGTFP varies across different areas: in the eastern, central, and western regions, for every 1 % increase in rural digitalization, the AGTFP increases by 2.65 %, 1.53 %, and 0.82 %, respectively. (2) Rural digitalization fosters an increase in AGTFP by stimulating rural entrepreneurial activity, with the mediation effect of rural entrepreneurial activity accounting for 3.34 % of the total effect. (3) Utilizing a threshold model, observations indicate that when rural digitalization surpasses the first threshold of 0.3200, the AGTFP coefficient escalates from 0.0462 to 0.7519. However, when rural digitalization exceeds the second threshold of 0.7118, this coefficient declines to 0.2429, signifying a nonlinear trend in the marginal effect of rural digitalization on AGTFP—initial enhancement followed by attenuation. (4) In the spatial model analysis, the study confirms spatial spillover effects of rural digitalization on AGTFP, indicating variations in spatial effects among different matrices. However, the indirect effects of rural digitalization on AGTFP, mainly influenced by the neighboring counties' digitalization levels, contribute more significantly than the direct effects. Based on these conclusions, this paper proposes augmenting investments in rural digitalization, implementing diversified rural digitalization schemes, invigorating rural entrepreneurial activity, and harmonizing regional digital development as novel approaches to enhance AGTFP, thereby fostering rural economic development.

Antidyslipidaemic evaluation of coagulin C and withacoagulin isolated from Withania coagulans (Stocks) dunal berries in hypertension induced secondary dyslipidemia in albino mice

Vascular diseases like hypertension has often been associated with dyslipidemia. Sustained elevated blood pressure for not less than four weeks develops gross irregularities inside arteriolar lumen. The pathological changes might be due to intimal arteriosclerotic thickening causing tapering of the structural narrowing along the arterioles. It might also be due to occurrence of irregular damage in the vascular structure from focal arteriolar constriction and lead to secondary dyslipidemia. The pharmacological intervention may lead to rectification and therapeutic benefit against dyslipidemia.The withanolides coagulin C and withacoagulin were isolated by flash chromatography from the extracts of Withania coagulans (Stocks) Dunal berries. The withanolides were characterized using 1H NMR and 13C NMR, UV and mass spectrometry and confirmed as coagulin C and withacoagulin. The oral toxicity of coagulin C and withacoagulin were investigated in albino mice followed by their antidyslipidemic activity with two dose levels i.e. 25 mg/kg and 50 mg/Kg p.o. This dyslipidemia was secondary to hypertension which was developed by DOCA salt model (25 mg/kg; s.c.+ 2% NaCl). Mice were administered dose of 10, 50 and 500 mg/kg coagulin C and withacoagulin orally for 28 days daily for sub-acute toxicity effect.Coagulin C and withacoagulin were found to be tolerated upto 2000 mg/kg p.o. during acute toxicity study in mice. Coagulin C and withacoagulin were claimed to possess No-Observed Adverse Effect Level (NOEL) at the dose of 500 mg/kg orally. The high dose (50 mg/Kg) withacoagulin has highly significant difference in total cholesterol, triglyceride, HDL, LDL and VLDL levels in comparison to disease control group along with highly significant difference in triglyceride and VLDL level compared to animals of vehicle control group. Coagulin C at both the low (25 mg/Kg) and high dose (50 mg/Kg) have highly significant difference in comparison to vehicle control, disease control and positive control in controlling total cholesterol, triglyceride, LDL and VLDL levels in the experimental animals indicating that coagulin C is not much as effective as withacoagulin in the normalization of altered lipid profile of the experimental animals.On the basis of spectroscopic analysis the isolated compounds from Withania coagulans (Stocks) Dunal berries were confirmed to be coagulin C and withacoagulin. Acute oral toxicity test in mice was found to have safe profile even at high dose for both the compounds. On development of secondary dyslipidemia due to DOCA salt induced hypertension in albino mice, both the isolated compounds showed different degree of correction in the altered lipid profile of the animals. Whereas withacoagulin has been found to have more significant and successful in controlling the altered lipid profile, coagulin C has only marginal effect. The docking studies also confirm the result and hence it can be suggested that withacoagulin is better than coagulin C in managing the alteration of lipid profile of the experimental mice.

Tipping point analysis for the between-arm correlation in an arm-based evidence synthesis

Systematic reviews and meta-analyses are essential tools in contemporary evidence-based medicine, synthesizing evidence from various sources to better inform clinical decision-making. However, the conclusions from different meta-analyses on the same topic can be discrepant, which has raised concerns about their reliability. One reason is that the result of a meta-analysis is sensitive to factors such as study inclusion/exclusion criteria and model assumptions. The arm-based meta-analysis model is growing in importance due to its advantage of including single-arm studies and historical controls with estimation efficiency and its flexibility in drawing conclusions with both marginal and conditional effect measures. Despite its benefits, the inference may heavily depend on the heterogeneity parameters that reflect design and model assumptions. This article aims to evaluate the robustness of meta-analyses using the arm-based model within a Bayesian framework. Specifically, we develop a tipping point analysis of the between-arm correlation parameter to assess the robustness of meta-analysis results. Additionally, we introduce some visualization tools to intuitively display its impact on meta-analysis results. We demonstrate the application of these tools in three real-world meta-analyses, one of which includes single-arm studies.

Are gaps in rates of retention on buprenorphine for treatment of opioid use disorder closing among veterans across different races and ethnicities? A retrospective cohort study

IntroductionThe U.S. Veterans Health Administration has undertaken several initiatives to improve veterans' access to and retention on buprenorphine because it prevents overdose and reduces drug-related morbidity. We aimed to determine whether improvements in retention duration over time was equitable across veterans of different races and ethnicities. MethodsThis retrospective cohort study was conducted among veterans who initiated buprenorphine from federal fiscal years (FY) 2006 to 2020 after diagnosis of opioid use disorder. Using an accelerated failure time model, we estimated the association between time to buprenorphine discontinuation and FY of initiation, race and ethnicity, and other control covariates. We followed veterans from buprenorphine initiation until they discontinued or had a censoring event. We then estimated the predicted median days retained on buprenorphine, the average marginal effect of initiating in a later FY, the same measure by race and ethnicity, the incremental effect of the various racial and ethnic identities in contrast to non-Hispanic White, and the total change in the size of the gap over the 15 years of the study between veterans with a minoritized racial or ethnic identity compared to non-Hispanic White veterans. ResultsMost of the 31,797 veterans in the sample were non-Hispanic White (74.5 %), from urban areas (83.5 %), male (92.0 %), and had significant comorbidities, most frequently anxiety disorders (51.0 %) and depression (63.0 %). Overall, 49.8 % of veterans were retained at least 180 days. The average marginal effect of FY was 7.0 days [95%CI:5.3, 8.8] but was significantly smaller among veterans identifying as Black or African American [3.2 days; 95%CI:2.4, 4.1] or Asian [3.6 days; 95%CI:1.6, 5.7] compared to veterans who identify as non-Hispanic White [7.9 days; 95%CI:5.9, 9.9]. Additional measures of change were significant for veterans identifying as Hispanic White or with two or more races. ConclusionAlthough buprenorphine retention in OUD treatment improved for all veterans over the 15-year study period, veterans from most minoritized racial and ethnic groups fell further behind as gains in duration on therapy accrued primarily to non-Hispanic White veterans. Targeted interventions addressing specific challenges experienced by veterans with minoritized identities are needed to close gaps in retention on buprenorphine.

Financial inclusion and the global net-zero emissions agenda: Does governance quality matter?

We inspect the impact of financial inclusion on carbon (CO2) emissions and the role that quality of governance plays using a global dataset from 119 countries between 2004 and 2020. We address endogeneity using the dynamic two-step generalized method of moment estimator and further test the robustness of results using the Driscol-Kraay estimator, which is crucial for addressing cross-sectional and temporal dependence. The findings showed that financial inclusion and quality of governance exhibited a positive and significant impact on CO2 emissions. Further analysis shows that the impact of financial inclusion and governance on CO2 emissions varies across countries at different stages of economic development. We also documented significant variations in the results across six geographical regions. Also, the evidence from moderation and marginal effect analysis revealed that the marginal effect of financial inclusion on CO2 emissions is contingent on governance quality and that improving governance quality (scores) conditions financial inclusion to minimize CO2 emissions across the globe. We, therefore, demonstrate that in countries with relatively higher (better) governance scores, such as the United Kingdom, Denmark, Singapore, and New Zealand, financial inclusion significantly mitigates CO2 emissions compared to countries with relatively lower (weak) governance scores, such as Iraq, Zimbabwe, Ghana, and Chad. Finally, mediation analysis also highlights that the effect of financial inclusion on CO2 emissions is mediated by renewable energy consumption, industrialization, and household consumption. The policy implications are discussed.

Average treatment effects on binary outcomes with stochastic covariates.

When evaluating the effect of psychological treatments on a dichotomous outcome variable in a randomized controlled trial (RCT), covariate adjustment using logistic regression models is often applied. In the presence of covariates, average marginal effects (AMEs) are often preferred over odds ratios, as AMEs yield a clearer substantive and causal interpretation. However, standard error computation of AMEs neglects sampling-based uncertainty (i.e., covariate values are assumed to be fixed over repeated sampling), which leads to underestimation of AME standard errors in other generalized linear models (e.g., Poisson regression). In this paper, we present and compare approaches allowing for stochastic (i.e., randomly sampled) covariates in models for binary outcomes. In a simulation study, we investigated the quality of the AME and stochastic-covariate approaches focusing on statistical inference in finite samples. Our results indicate that the fixed-covariate approach provides reliable results only if there is no heterogeneity in interindividual treatment effects (i.e., presence of treatment-covariate interactions), while the stochastic-covariate approaches are preferable in all other simulated conditions. We provide an illustrative example from clinical psychology investigating the effect of a cognitive bias modification training on post-traumatic stress disorder while accounting for patients' anxiety using an RCT.

Why leave items in the shopping cart? The impact of consumer filtering behavior

Online product information provides crucial cues for consumer shopping behavior; however, the impact of consumer-side information manipulation on non-purchase behavior (e.g., shopping cart abandonment) remains unclear. Filtering, a common manipulation strategy, was initially considered synonymous with searching, both of which contribute to consumer purchase behavior. However, recent research suggests significant differences, particularly in terms of cost and product matching. This study explores how such differences affect information manipulation and subsequently shape shopping cart abandonment, drawing on information foraging theory. Based on the premise that a forager's interaction with the environment is mediated by cognition, we find that consumer filtering behavior influences perceptions of serendipity (i.e., discovering unexpected items) and similarity (i.e., encountering similar items), thereby influencing shopping cart abandonment. Mediation analyses reveal that perceived serendipity and similarity are equally potent mediators. Marginal effects analyses demonstrate that a one standard deviation increase in consumer perceptions of serendipity (similarity) in filtering results increases the likelihood of shopping cart abandonment by 32.2% (22.1%). Theoretical contributions and practical insights for information behavior researchers and digital marketers are also provided.

Two are Better Than One but Three is Best: Fast-Tracking the Attainment of the Sustainable Development Goals (SDGs) Among In-School Adolescents in Nigeria

BackgroundWith 60% of Africa’s population under the age of 25 years, investing in youth will accelerate progress towards achieving the Sustainable Development Goals (SDGs). The United Nations concept of ‘Development Accelerators’ is operationalized by examining factors associated with multiple SDGs among adolescents in Nigeria.MethodologyThrough data collected on the health of 1800 adolescents in Southwest Nigeria (Ibadan), ten SDG targets were identified. Accelerator protective factors that could lead to the attainment of two or more SDG targets were identified. Associations were assessed using multivariable logistic regression adjusting for sociodemographic covariates and multiple testing. Cumulative effects were tested by marginal effects modelling.ResultsParticipants’ mean age was 15.02 years (SD = 2.27). Family (parenting support), environmental (no survival work and food security) and school (safe schools) related factors emerged as development accelerators. For seven of the identified SDG-aligned targets, a combination of two or more accelerator factors showed cumulative positive associations, suggesting accelerator synergies with a combination of three accelerators showing the greatest increase. For instance, perceiving the school environment as safe, being food secure and having optimal mental health was associated with an 67% chance of not using psychoactive substances. While with safe school alone it was 39% (29%-51%), with food security alone it was 42% (31%-54%) and with optimal mental health alone it was 54% (42%-66%).ConclusionSeveral development accelerators related to family, environmental and school factors can have additive effects on the attainment of the SDGs amongst adolescents in Nigeria. This has practical and policy utility in the fastest growing economy in Africa.

Laboratory evaluation of performances and thermo-oxidative aging characteristics of high-viscosity modified asphalt

High construction temperatures and complex application conditions make the high-viscosity modified asphalt (HVMA) susceptible to aging. This work presents a comprehensive investigation of the performances and thermo-oxidative aging characteristics of HVMA. Fistly, an instant high-viscosity modifier (HVM) was synthesized and then optimized by entropy weight method. The modification mechanism and high- and low-temperature performances of HVMAs were investigated by the Fourier transform infrared spectroscopy (FTIR), temperature sweep, and low temperature creep tests. Besides, thermo-oxidative aging characteristics were evaluated by the frequency sweep, multiple stress creep recovery (MSCR) and fluorescence microscopy (FM) tests. Results shows that the recommended formulation of instant HVMA (HVMA-I) was 12 % instant HVM and 0.2 % stabilizer. Grafting and cross-linking reactions involved in HVMA-I, thus ensuring the excellent high- and low-temperature performances. The thermo-oxidative aging of HVMA consisted of the modifier degradation and the binder oxidation. Short-term aging produced a marginal effect as a fluctuating change direction for complex modulus. Long-term aging had pronounced effects on the performances of HVMA. At the macroscopic level, the complex modulus was increased and the nonrecoverable creep compliance was decreased; at the microscopic level, the fluorescence area was reduced and phase network was degraded.