Direct and Indirect Effects of Youth Sports Participation on Emotional Intelligence, Self-Esteem, and Life Satisfaction.

The present study investigated the mediating effects of emotional intelligence and self-esteem between youth sports participation and life satisfaction, as well as the comparative effects of different types of sports involvement (team, individual, and non-participation) on these selected variables. A sample of 1053 Portuguese adolescents (612 girls and 441 boys), aged between 12 and 18 years (M = 14.40; SD = 1.55), completed the following self-report measures: the Wong and Law Emotional Intelligence Scale, the Rosenberg Self-Esteem Scale, and the Satisfaction with Life Scale. The structural equation modeling results indicated a complete mediating role of two emotional intelligence dimensions (use of emotion and self-emotional appraisal) and self-esteem in the relationship between sports participation and adolescents' life satisfaction. Team sport participants reported higher emotional intelligence and self-esteem scores than their non-sport participant counterparts who revealed lower levels of emotion use than their individual sport participant peers. These findings provide novel insights into the potential emotional and psychological mechanisms underlying the association between youth sports participation and life satisfaction.

Mediation analysis using incomplete information from publicly available data sources.

Our work was motivated by the question whether, and to what extent, well-established risk factors mediate the racial disparity observed for colorectal cancer (CRC) incidence in the United States. Mediation analysis examines the relationships between an exposure, a mediator and an outcome. All available methods require access to a single complete data set with these three variables. However, because population-based studies usually include few non-White participants, these approaches have limited utility in answering our motivating question. Recently, we developed novel methods to integrate several data sets with incomplete information for mediation analysis. These methods have two limitations: (i) they only consider a single mediator and (ii) they require a data set containing individual-level data on the mediator and exposure (and possibly confounders) obtained by independent and identically distributed sampling from the target population. Here, we propose a new method for mediation analysis with several different data sets that accommodates complex survey and registry data, and allows for multiple mediators. The proposed approach yields unbiased causal effects estimates and confidence intervals with nominal coverage in simulations. We apply our method to data from U.S. cancer registries, a U.S.-population-representative survey and summary level odds-ratio estimates, to rigorously evaluate what proportion of the difference in CRC risk between non-Hispanic Whites and Blacks is mediated by three potentially modifiable risk factors (CRC screening history, body mass index, and regular aspirin use).

[Direct and Indirect Effects of Land Use on Dissolved Organic Matter in a Typical Karst River].

Land use can directly affect the abundance of riverine dissolved organic matter (DOM) by transporting terrestrial organic matter to rivers and can also indirectly enhance local production of DOM by increasing riverine nutrient loading. This study investigated the characteristics and spatial distribution of DOM components in the Furong River during the rainy season (July) using ultraviolet-visible light absorption spectroscopy (UV-VIS) and three-dimensional excitation emission matrix fluorescence spectroscopy-parallel factor analysis (EEM-PARAFAC) techniques. Furthermore, correlation analysis and the partial least squares path model (PLS-PM) were used to identify and quantify the direct and indirect impacts of land use on DOM at multiple scales. The results revealed that:① the direct effects of land use on DOM were generally stronger than the indirect effects. ② The responses of different DOM components to riverine nutrient status and land use varied, with dissolved organic carbon (DOC) and colored dissolved organic matter (CDOM) components being more susceptible to riverine nutrient status and fluorescent dissolved organic matter (FDOM) being more sensitive to land use. ③ The direct impact intensity of land use on DOC and CDOM fluctuated slightly with the spatial scale, but the total impact intensity had no visible spatial scale difference, and the direct impact intensity on the FDOM component decreased with the increase in spatial scale. ④ Dryland, urban and other construction land, patch density (PD), edge density (ED), and Shannon's diversity index (SHDI) were typical land use metrics that exacerbated DOM abundance, whereas paddy field, shrubland, largest patch index (LPI), and aggregation index (AI) were typical land use metrics that effectively mitigated DOM abundance. Total nitrogen (TN), nitrate nitrogen (NO3--N), and dissolved total phosphorus (DTP) were water quality parameters that were significantly affected by land use and were closely related to DOM components, that is, nitrogen and phosphorus played an important "intermediary" role in "land use-riverine DOM." FDOM could be used as indicators to measure the strength of terrestrial organic matter directly input to rivers by land use.

An integrative perspective on fish health: Environmental and anthropogenic pathways affecting fish stress.

Multifactorial studies assessing the cumulative effects of natural and anthropogenic stressors on individual stress response are crucial to understand how organisms and populations cope with environmental change. We tested direct and indirect causal pathways through which environmental stressors affect the stress response of wild gilthead seabream in Mediterranean costal lagoons using an integrative PLS-PM approach. We integrated information on 10 environmental variables and 36 physiological variables into seven latent variables reflecting lagoons features and fish health. These variables concerned fish lipid reserves, somatic structure, inorganic contaminant loads, and individual trophic and stress response levels. This modelling approach allowed explaining 30 % of the variance within these 46 variables considered. More importantly, 54 % of fish stress response was explained by the dependent lagoon features, fish age, fish diet, fish reserve, fish structure and fish contaminant load latent variables included in our model. This integrative study sheds light on how individuals deal with contrasting environments and multiple ecological pressures.

Social, economic, and technical factors affecting CO2 emissions in Iran.

Most scholars support the increase in carbon dioxide (CO2) emissions as one of the major causes of the increase in global climate change. Therefore, reducing CO2 emissions from the main emitter countries, including Iran as the sixth emitter, is important to deal with the harmful effects of global climate change. Accordingly, the main aim of this paper was to analyze the social, economic, and technical factors affecting CO2 emissions in Iran. Previous studies on diverse variables affecting emissions are not very accurate and reliable as they do not consider indirect effects. This study applied a structural equation model (SEM) to estimate the direct and indirect impacts of factors on the emissions by panel data for 28 provinces of Iran from 2003 to 2019. According to geographical location, three distinct regions, the north, center, and south of Iran were considered. The findings suggest that a 1% increase in social factor directly increased CO2 emissions by 2.23% (in the north) and 1.58% (in the center), but indirectly reduced emissions by 0.41% (in the north) and 0.92% (in the center). Hence, the total effects of the social factor on CO2 emissions were estimated at 1.82%, and 0.66% in the northern, and central regions, respectively. In addition, the total effects of the economic factor on CO2 emissions were estimated at 1.52%, and 0.73% in those regions. The results of this study showed that the direct effects of a technical factor on CO2 emissions were negative in the north and center. However, they were positive in the south of Iran. Based on the empirical results of this study, three policy implications are discussed in order to control CO2 emissions in regional distinctions of Iran as follows: First, policymakers should pay attention to the social factor, i.e., the growth of human capital in the southern region with the aim of increasing sustainable development. Second, Iranian policymakers must prevent unilaterally increasing gross domestic product (GDP) and financial development in the north and center. Third, policymakers should pay attention to the technical factor, i.e., improving energy efficiency, as well as upgrading information and communications technology (ICT) in the northern and central regions, and limiting the technical factor in the southern region.

Effects of water depth on the biomass of two dominant submerged macrophyte species in floodplain lakes during flood and dry seasons.

Floodplain lakes share characteristics of both deep and shallow lakes throughout any given year. Seasonal fluctuations in their water depth drive changes in nutrients and total primary productivity, which directly and indirectly affect submerged macrophyte biomass. To investigate how water depth and environmental variables affect submerged macrophyte biomass, we surveyed six sub-lakes in the Poyang Lake floodplain, China, during the flood and dry seasons of 2021. Dominant submerged macrophytes include Vallisneria spinulosa and Hydrilla verticillata. The effect of water depth on the biomass of these macrophytes varied between the flood and dry seasons. In the flood season, there was a direct effect of water depth on biomass, while in the dry season only an indirect effect was observed. During the flood season, the direct effect of water depth on the biomass of V. spinulosa was less than the indirect effect, with water depth primarily affecting the total nitrogen, total phosphorus and water column transparency. Water depth directly, positively affected H. verticillata biomass, with this effect being greater than the indirect effect by affecting the carbon, nitrogen and phosphorus content in the water column and sediment. During the dry season, water depth affected H. verticillata biomass indirectly through sediment carbon and nitrogen content, while for V. spinulosa, the effect on biomass was indirect through carbon content of the sediment and water column. The main environmental variables affecting submerged macrophyte biomass in the Poyang Lake floodplain during the flood and dry seasons, and the mechanisms through which water depth affects dominant submerged macrophyte biomass, are identified. An understanding of these variables and mechanisms will enable improved management and restoration of wetland.

Climate-driven vegetation greening further reduces water availability in drylands.

Climate change alters surface water availability (WA; precipitation minus evapotranspiration, P - ET) and consequently impacts agricultural production and societal water needs, leading to increasing concerns on the sustainability of water use. Although the direct effects of climate change on WA have long been recognized and assessed, indirect climate effects occurring through adjustments in terrestrial vegetation are more subtle and not yet fully quantified. To address this knowledge gap, here we investigate the interplay between climate-induced changes in leaf area index (LAI) and ET and quantify its ultimate effect on WA during the period 1982-2016 at the global scale, using an ensemble of data-driven products and land surface models. We show that ~44% of the global vegetated land has experienced a significant increase in growing season-averaged LAI and climate change explains 33.5% of this greening signal. Such climate-induced greening has enhanced ET of 0.051 ± 0.067 mm year-2 (mean ± SD), further amplifying the ongoing increase in ET directly driven by variations in climatic factors over 36.8% of the globe, and thus exacerbating the decline in WA prominently in drylands. These findings highlight the indirect impact of positive feedbacks in the land-climate system on the decline of WA, and call for an in-depth evaluation of these phenomena in the design of local mitigation and adaptation plans.

Summary of volume 51: DNA damage and double-strand breaks.

DNA damage and breaks are events that happen to DNA which exert a variety of influence on cell physiology including inhibition of DNA synthesis, repair response, cell cycle effect and cell death. Thus, it is important to deepened understanding of these events. In volume 51, we discussed topics including (1) assays to detect double-strand breaks, (2) conditions leading to double-strand breaks, (3) effects of irradiation, (4) DNA structure and chromatins, and (5) direct and indirect effect on DNA. Contributing authors and a table of contents for volume 51 are mentioned. We also discuss further issues and topics that need to be featured in future volumes. These include DNA damage sensors, DNA damage response proteins, and double-strand break repair pathways.

Applied causal inference methods for sequential mediators.

BACKGROUND: Mediation analysis aims at estimating to what extent the effect of an exposure on an outcome is explained by a set of mediators on the causal pathway between the exposure and the outcome. The total effect of the exposure on the outcome can be decomposed into an indirect effect, i.e. the effect explained by the mediators jointly, and a direct effect, i.e. the effect unexplained by the mediators. However finer decompositions are possible in presence of independent or sequential mediators. METHODS: We review four statistical methods to analyse multiple sequential mediators, the inverse odds ratio weighting approach, the inverse probability weighting approach, the imputation approach and the extended imputation approach. These approaches are compared and implemented using a case-study with the aim to investigate the mediating role of adverse reproductive outcomes and infant respiratory infections in the effect of maternal pregnancy mental health on infant wheezing in the Ninfea birth cohort. RESULTS: Using the inverse odds ratio weighting approach, the direct effect of maternal depression or anxiety in pregnancy is equal to a 59% (95% CI: 27%,94%) increased prevalence of infant wheezing and the mediated effect through adverse reproductive outcomes is equal to a 3% (95% CI: -6%,12%) increased prevalence of infant wheezing. When including infant lower respiratory infections in the mediation pathway, the direct effect decreases to 57% (95% CI: 25%,92%) and the indirect effect increases to 5% (95% CI: -5%,15%). The estimates of the effects obtained using the weighting and the imputation approaches are similar. The extended imputation approach suggests that the small joint indirect effect through adverse reproductive outcomes and lower respiratory infections is due entirely to the contribution of infant lower respiratory infections, and not to an increased prevalence of adverse reproductive outcomes. CONCLUSIONS: The four methods revealed similar results of small mediating role of adverse reproductive outcomes and early respiratory tract infections in the effect of maternal pregnancy mental health on infant wheezing. The choice of the method depends on what is the effect of main interest, the type of the variables involved in the analysis (binary, categorical, count or continuous) and the confidence in specifying the models for the exposure, the mediators and the outcome.

Expanding the Direct and Indirect Effects Model of Writing (DIEW): Reading-Writing Relations, and Dynamic Relations As a Function of Measurement/Dimensions of Written Composition.

Within the context of the Direct and Indirect Effects model of Writing, we examined a dynamic relations hypothesis, which contends that the relations of component skills, including reading comprehension, to written composition vary as a function of dimensions of written composition. Specifically, we investigated (a) whether higher order cognitive skills (i.e., inference, perspective taking, and monitoring) are differentially related to three dimensions of written composition-writing quality, writing productivity, and correctness in writing; (b) whether reading comprehension is differentially related to the three dimensions of written composition after accounting for oral language, cognition, and transcription skills; and whether reading comprehension mediates the relations of discourse oral language and lexical literacy to the three dimensions of written composition; and (c) whether total effects of oral language, cognition, transcription, and reading comprehension vary for the three dimensions of written composition. Structural equation model results from 350 English-speaking second graders showed that higher order cognitive skills were differentially related to the three dimensions of written composition. Reading comprehension was related only to writing quality, but not to writing productivity or correctness in writing; and reading comprehension differentially mediated the relations of discourse oral language and lexical literacy to writing quality. Total effects of language, cognition, transcription, and reading comprehension varied largely for the three dimensions of written composition. These results support the dynamic relation hypothesis, role of reading in writing, and the importance of accounting for dimensions of written composition in a theoretical model of writing.

Nutrient potentiate the responses of plankton community structure and metabolites to cadmium: A microcosm study.

Metal pollution is a worldwide concern and may pose risks to aquatic organisms, communities, and ecosystems. The toxic effects of metals at the organism level are relatively clear. However, their impacts at the community level are still poorly understood, especially with concurred eutrophication in surface water. In the present study, the effects of Cd on the plankton community structure and function under varying nutrient conditions were evaluated using a microcosm study. The employed concentrations of Cd and nutrient were based on the values currently measured in the freshwater ecosystem. For the plankton structure, our results showed that the Chl a concentration, the abundances of total phytoplankton, Cyanophyta, and Chlorophyta, and the abundance of Copepoda decreased by Cd consistently. The Cyanophyta Oscillatoria tenuis and Copepoda nauplius were the most sensitive species to Cd in the phytoplankton and zooplankton community, respectively. For the community effects, we found the inhibitory effects of Cd on the photosystem II (PSII) activity of phytoplankton community because of the consistent decrease in the chlorophyll fluorescence parameters (Fv/Fm, Y(Ⅱ), and ETR). Furthermore, the reductions of DOC and pH by Cd were only found in the high nutrient condition, which indicated that the toxic effects of Cd on the community structure and community metabolites were aggravated by the increased nutrient. This study emphasizes the importance of considering nutrient conditions when assessing the metal ecotoxicological effects at environmentally relevant concentrations.

The role of MicroRNA networks in tissue-specific direct and indirect effects of metformin and its application.

Metformin is a first-line oral antidiabetic agent that results in clear benefits in relation to glucose metabolism and diabetes-related complications. The specific regulatory details and mechanisms underlying these benefits are still unclear and require further investigation. There is recent mounting evidence that metformin has pleiotropic effects on the target tissue development in metabolic organs, including adipose tissue, the gastrointestinal tract and the liver. The mechanism of actions of metformin are divided into direct effects on target tissues and indirect effects via non-targeted tissues. MicroRNAs (miRNAs) are a class of endogenous, noncoding, negative gene regulators that have emerged as important regulators of a number of diseases, including type 2 diabetes mellitus (T2DM). Metformin is involved in many aspects of miRNA regulation, and metformin treatment in T2DM should be associated with other miRNA targets. A large number of miRNAs regulation by metformin in target tissues with either direct or indirect effects has gradually been revealed in the context of numerous diseases and has gradually received increasing attention. This paper thoroughly reviews the current knowledge about the role of miRNA networks in the tissue-specific direct and indirect effects of metformin. Furthermore, this knowledge provides a novel theoretical basis and suggests therapeutic targets for the clinical treatment of metformin and miRNA regulators in the prevention and treatment of cancer, cardiovascular disorders, diabetes and its complications.

Geriatric impairments were directly and indirectly associated with mortality in older patients with cancer: a structural equation analysis.

OBJECTIVES: We assessed the direct and indirect effects between six geriatric domains and 6- and 12-month mortality in older cancer patients. STUDY DESIGN AND SETTING: We included cancer patients aged ≥70 years from the Elderly Cancer Patients cohort, referred for geriatric assessment between 2007 and 2016. We used structural equation modelling to examine the interrelationships between six geriatric domains (function and mobility, nutrition, cognition, mood, comorbidities and polypharmacy, and social support) and the direct and indirect relationships between these domains, the cancer stage, site, and treatment on the one hand and mortality on the other. RESULTS: The analysis included 1,434 patients (mean age: 80 ± 5.6 years; women: 48%; main cancer sites: digestive tract [36.2%], urinary tract and prostate [26.6%], and breast [16.5%]; metastatic cancer: 48%). Direct relationships to 6- and 12-month mortality were identified for functional impairment (standardized coefficient [SC]: 0.37 [P < 0.001] and 0.32 [P < 0.001], respectively), poor nutritional status (SC: 0.11 [P = 0.005] and 0.14 [P = 0.001]), poor social support (SC = 0.07 [P = 0.08] and 0.09 [P = 0.02]), cancer site, stage, and treatment. The effects of comorbidities, cognitive impairment, and depression on mortality were mediated by functional and nutritional status. CONCLUSION: In older cancer patients, functional and nutritional impairments were the strongest direct prognostic geriatric factors for mortality.

Lift the Veil of Breast Cancers Using 4 or Fewer Critical Genes.

Known genes in the breast cancer study literature could not be confirmed whether they are vital to breast cancer formations due to lack of convincing accuracy, although they may be biologically directly related to breast cancer based on present biological knowledge. It is hoped vital genes can be identified with the highest possible accuracy, for example, 100% accuracy and convincing causal patterns beyond what has been known in breast cancer. One hope is that finding gene-gene interaction signatures and functional effects may solve the puzzle. This research uses a recently developed competing linear factor analysis method in differentially expressed gene detection to advance the study of breast cancer formation. Surprisingly, 3 genes are detected to be differentially expressed in TNBC and non-TNBC (Her2, Luminal A, Luminal B) samples with 100% sensitivity and 100% specificity in 1 study of triple-negative breast cancers (TNBC, with 54 675 genes and 265 samples). These 3 genes show a clear signature pattern of how TNBC patients can be grouped. For another TNBC study (with 54 673 genes and 66 samples), 4 genes bring the same accuracy of 100% sensitivity and 100% specificity. Four genes are found to have the same accuracy of 100% sensitivity and 100% specificity in 1 breast cancer study (with 54 675 genes and 121 samples), and the same 4 genes bring an accuracy of 100% sensitivity and 96.5% specificity in the fourth breast cancer study (with 60 483 genes and 1217 samples). These results show the 4-gene-based classifiers are robust and accurate. The detected genes naturally classify patients into subtypes, for example, 7 subtypes. These findings demonstrate the clearest gene-gene interaction patterns and functional effects with the smallest numbers of genes and the highest accuracy compared with findings reported in the literature. The 4 genes are considered to be essential for breast cancer studies and practice. They can provide focused, targeted researches and precision medicine for each subtype of breast cancer. New breast cancer disease types may be detected using the classified subtypes, and hence new effective therapies can be developed.

Large herbivores facilitate a dominant grassland forb via multiple indirect effects.

While large herbivores are critically important components of terrestrial ecosystems and can have pronounced top-down effects on plants, our understanding of the underlying mechanisms driving these effects remains incomplete. Large herbivores can alter plant growth, reproduction, and abundance through direct effects (predominantly consumption) and through indirect effects via altered interactions with abiotic factors and other species. We know considerably less about these indirect effects than the direct effects. Here, we integrate medium- and small-scale field experiments to investigate how a large vertebrate herbivore, cattle (Bos taurus), affects the aboveground biomass of a dominant forb species, Artemisia scoparia, via diverse direct and indirect pathways in a temperate grassland in northeast China. Although cattle consumed this forb, its biomass increased significantly in response to grazing, due to multiple indirect positive effects that outweighed the direct negative effects of consumption. Cattle preferentially consumed the competing grass Leymus chinensis, and altered Artemisia microhabitats by reducing total plant cover and litter biomass and by increasing the abundance of co-occurring ant species (e.g., Formica spp. and Lasius spp.). This led to additional indirect positive effects on A. scoparia likely due to (1) increased light availability in understory layers and other limiting resources (e.g., soil nutrients and moisture) caused by removal of competitors and plant litter at the soil surface and (2) the changes in resource availability (e.g., soil nutrients and moisture) associated with ant colonies. Our results show that large herbivores can affect plant growth not only via direct consumption, but also via multiple indirect effects. Focusing on the causes and consequences of herbivore-induced indirect effects will not only help us to better understand the influence of these animals in ecological systems, but will also lead to more effective land management and conservation practices in the regions they inhabit.

Nonlinear mediation analysis with high-dimensional mediators whose causal structure is unknown.

With multiple possible mediators on the causal pathway from a treatment to an outcome, we consider the problem of decomposing the effects along multiple possible causal path(s) through each distinct mediator. Under a path-specific effects framework, such fine-grained decompositions necessitate stringent assumptions, such as correctly specifying the causal structure among the mediators, and no unobserved confounding among the mediators. In contrast, interventional direct and indirect effects for multiple mediators can be identified under much weaker conditions, while providing scientifically relevant causal interpretations. Nonetheless, current estimation approaches require (correctly) specifying a model for the joint mediator distribution, which can be difficult when there is a high-dimensional set of possibly continuous and noncontinuous mediators. In this article, we avoid the need to model this distribution, by developing a definition of interventional effects previously suggested for longitudinal mediation. We propose a novel estimation strategy that uses nonparametric estimates of the (counterfactual) mediator distributions. Noncontinuous outcomes can be accommodated using nonlinear outcome models. Estimation proceeds via Monte Carlo integration. The procedure is illustrated using publicly available genomic data to assess the causal effect of a microRNA expression on the 3-month mortality of brain cancer patients that is potentially mediated by expression values of multiple genes.

Spatial Spillover Effects of Renewable Energy on Carbon Emissions in Less-developed Areas of China.

The purpose of this paper is to determine the spatial spillover effects of renewable energy on carbon emissions in China's less-developed areas. However, few studies have considered this issue from the perspective of less-developed areas. Based on panel data of 21 provinces in China from 2000 to 2017, this paper analyzes the spatial spillover effects of renewable energy on carbon emissions using Moran's I and Spatial Durbin Model (SDM). The results suggest that, first, Moran's I ranges from 0.378 to 0.519, Moran scatter plot presents that provinces are located in the high-high (HH) and low-low (LL) quadrants, indicating provincial carbon emissions in the study area have a significant spatial correlation and agglomeration. Second, under the three matrices, the direct effect coefficients of renewable energy are -0.2522, -0.2639 and -0.2601, this shows that renewable energy is beneficial to local carbon emissions reduction. In contrast, the indirect effect coefficients of renewable energy are 0.0605, 0.1012 and 0.1125, which means higher renewable energy consumption in a single area is conducive to the improvement of carbon emissions to neighbouring areas. Third, urbanization, industrialization, physical capital and other variables have different impacts on local and nearby carbon emissions. This study provides empirical evidence to achieve carbon emission reduction targets by government policymakers.

A generalist nematode destabilises plant competition: no evidence for direct effects, but strong evidence for indirect effects on rhizobium abundance.

Difficulties quantifying pathogen load and mutualist abundance limit our ability to connect disease dynamics to host community ecology. For example, specific predictions about how differential pathogen load is hypothesised to drive host competitive outcomes are rarely tested. Additionally, although infection is known to affect mutualists, we rarely measure the magnitude of pathogen effects on mutualist abundance across host competitive contexts. We tested for both mechanisms in a plant-rhizobia-nematode system. We paired the legume Medicago lupulina with intraspecific and interspecific plant competitors, with and without a generalist nematode parasite Meloidogyne sp. Relative change in plant biomass was used to determine how nematode inoculation affected plant competitive outcomes. We counted nematode galls to test for direct effects of parasitism on plant competition and rhizobia nodules to test for indirect effects of nematode presence on rhizobium abundance. Parasites were destabilising despite similar nematode load across competition treatments. During interspecific compared with intraspecific competition, nematode inoculation decreased nodulation on M. lupulina, increased nodulation on Trifolium repens and had no effect on nodulation on Chamaecrista fasciculata. We found no support for hypothesised direct effects of nematode load on competitive outcomes and strong but idiosyncratic indirect effects of nematode inoculation on rhizobium abundance.

Path Analysis to Assess Socio-Economic and Mitigation Measure Determinants for Daily Coronavirus Infections.

(1) Background: With the rapid global spread of the coronavirus disease 2019 (COVID-19) and the relatively high daily cases recorded in a short time compared to other types of seasonal flu, the world remains under continuous threat unless we identify the key factors that contribute to these unexpected records. This identification is important for developing effective criteria and plans to reduce the spread of the COVID-19 pandemic and can guide national authorities to tighten or reduce mitigation measures, in addition to spreading awareness of the important factors that contribute to the propagation of the disease. (2) Methods: The data represents the daily infections (210 days) in four different countries (China, Italy, Iran, and Lebanon) taken approximately in the same duration, between January and March 2020. Path analysis was implemented on the data to detect the significant factors that affect the daily COVID-19 infections. (3) Results: The path coefficients show that quarantine commitment (ß = -0.823) and full lockdown measures (ß = -0.775) have the largest direct effect on COVID-19 daily infections. The results also show that more experience (ß = -0.35), density in society (ß = -0.288), medical resources (ß = 0.136), and economic resources (ß = 0.142) have indirect effects on daily COVID-19 infections. (4) Conclusions: The COVID-19 daily infections directly decrease with complete lockdown measures, quarantine commitment, wearing masks, and social distancing. COVID-19 daily cases are indirectly associated with population density, special events, previous experience, technology used, economic resources, and medical resources.

The impact of adjusting for pure predictors of exposure, mediator, and outcome on the variance of natural direct and indirect effect estimators.

It is now well established that adjusting for pure predictors of the outcome, in addition to confounders, allows unbiased estimation of the total exposure effect on an outcome with generally reduced standard errors (SEs). However, no analogous results have been derived for mediation analysis. Considering the simplest linear regression setting and the ordinary least square estimator, we obtained theoretical results showing that adjusting for pure predictors of the outcome, in addition to confounders, allows unbiased estimation of the natural indirect effect (NIE) and the natural direct effect (NDE) on the difference scale with reduced SEs. Adjusting for pure predictors of the mediator increases the SE of the NDE's estimator, but may increase or decrease the variance of the NIE's estimator. Adjusting for pure predictors of the exposure increases the variance of estimators of the NIE and NDE. Simulation studies were used to confirm and extend these results to the case where the mediator or the outcome is binary. Additional simulations were conducted to explore scenarios featuring an exposure-mediator interaction as well as the relative risk and odds ratio scales for the case of binary mediator and outcome. Both a regression approach and an inverse probability weighting approach were considered in the simulation study. A real-data illustration employing data from the Canadian Study of Health and Aging is provided. This analysis is concerned with the mediating effect of vitamin D in the effect of physical activity on dementia and its results are overall consistent with the theoretical and empirical findings.