Methods For Mediation Analysis Research Articles

Dissecting the genetic basis and mechanisms underlying the associations between multiple extrahepatic factors and autoimmune liver diseases

BackgroundAutoimmune liver diseases (AILDs) encompass autoimmune hepatitis (AIH), primary biliary cholangitis (PBC), and primary sclerosing cholangitis (PSC). The onset of these diseases is fundamentally influenced by genetic susceptibility. Although various extrahepatic factors are potentially linked to AILDs, the genetic underpinnings and mechanisms of these associations remain unclear. MethodsUtilizing large-scale genome-wide association study (GWAS) data, this study systematically investigated the relationships between extrahepatic autoimmune diseases (EHAIDs), immune cells, and various triggering factors with AILDs. Mendelian randomization (MR) was employed to assess the causal effects of these extrahepatic factors on AILDs, complemented by linkage disequilibrium score (LDSC) regression to uncover shared genetic architecture and causal effects underlying the associations between autoimmune diseases. We employed colocalization, enrichment analysis, and protein-protein interaction (PPI) network to identify the functions of shared loci. Additionally, we proposed that activated immune cells in the circulation may contribute to liver and biliary tract inflammation via migration, mediating the impact of extrahepatic factors on AILDs. This hypothesis was tested using two mediation analysis methods: two-step MR (TSMR) and multivariable MR (MVMR). ResultsCausal associations between multiple extrahepatic factors and AILDs were identified. Notably, CD27+ B cells were found to be a risk factor for PBC, while PSC progression was associated with CD28+ CD8+ T cells exhaustion and increased levels of CD28- CD8+ T cells. Mediation analyses revealed 64 pathways via TSMR and 15 pathways via MVMR, indicating that the effects of extrahepatic factors on AILDs may be mediated by circulating immune cells. The shared genetic architecture also contributed to these associations. Analysis of shared loci and gene functions identified ATXN2 as being shared between PBC and 9 EHAIDs, while SH2B3 and PSMG1 were shared with 6 and 5 EHAIDs, respectively, in PSC. ConclusionsOur research compared three distinct AILDs, enhancing the understanding of their etiology and providing new evidence on risk factors, diagnostic markers, and potential therapeutic targets.

Factors influencing COVID-19 vaccination intentions and mediating effects among older adults in Southwest China

This study examines the factors influencing COVID-19 vaccination intentions among Chinese residents over the age of 60, with a focus on the mediating roles of Health Beliefs and Cues to Vaccination Action in the relationship between vaccine knowledge and vaccination intentions. We conducted a cross-sectional online survey involving 1,305 participants from Southwest China. Multiple logistic regression analysis identified potential determinants of vaccination intention, including socioeconomic characteristics, knowledge, health beliefs, and cues to vaccination action. Furthermore, mediation analysis using the causal mediation analysis method explored the mediating effects within the knowledge-to-intention pathway. Vaccination intention and its related factors: among the 1212 elderly people included in the study, 92.9% expressed willingness to receive the COVID-19 vaccine. Main factors influencing their vaccination willingness included Residency (urban vs. rural, OR = 0.47, p < 0.01), Age (75 + vs. others, OR = 0.41, p < 0.05), Marital status (OR = 0.36, p < 0.01), Occupation ( business/service vs. others, OR = 0.33, p < 0.05), Awareness of vaccine effectiveness (OR = 1.23, p < 0.01), Cues to vaccination action (OR = 1.31, p < 0.01) and COVID-19 related knowledge (OR = 1.06, p < 0.01). The analysis revealed two significant mediators—Health Beliefs and Cues to Vaccination Action. These mediators (p<0.05 for both natural indirect effect and natural direct effect) acted along two key pathways: (1) From Knowledge of COVID-19 to Health Beliefs to Vaccination Intention: Natural Direct Effects (NDE) ranged from 0.012 to 0.016, with Natural Indirect Effects (NIE) from 0.001 to 0.003, indicating that mediators accounted for 4% to 18% of the total effect. (2) From Knowledge of COVID-19 to Cues of Vaccination Action to Vaccination Intention: NDE ranged from 0.012 to 0.016 and NIE from 0.002 to 0.003, with mediators accounting for 9% to 20% of the effect. The intention to vaccinate against COVID-19 among older adults varies significantly based on socioeconomic and health belief factors. The study identifies health beliefs and cues to action not only as direct contributors but also as crucial mediators in the pathway from knowledge to vaccination intention among older individuals. These findings can extend our understanding of the impact of sociodemographic factors and health beliefs on the COVID-19 vaccination willingness among older adults.

Occupational class difference in COVID-19 symptoms in France: contribution of work-related exposures

Abstract Background The association between socio-occupational class and SARS-CoV-2 infection remains inconclusive and may depend on the setting and the pandemic stage. Our study aims to quantify self-reported COVID-19 symptoms by occupational class (OC) in spring 2020 in France and explain observed differences using work-related risk factors. Methods We analyzed data from the EpiCoV population-based cohort, comprising 46,849 active workers aged 18-64 in metropolitan France. COVID-19 symptoms were sudden loss of taste/smell, fever with cough, fever with shortness of breath, or fever with chest oppression. Separating regions highly affected by COVID-19 from other regions, we related OC with reporting of COVID-19 symptoms and assessed the mediation effect of work-related SARS-CoV-2 exposures (contact with the public, using public transportation, self-perceived exposure) using the Karlson-Holm-Breen mediation analysis method. Results During the study period, 7.1% of the workers reported COVID-19 symptoms. In both regions, work-related SARS-CoV-2 exposures were related to higher reporting of symptoms, and those exposures were more prevalent in the lowest than in the highest OCs. However, the association of OC with reporting symptoms was not the same in the two regions. In less affected regions, the lowest OC reported COVID-19 symptoms less often than the highest OC, whereas in highly affected regions, symptoms were more frequent in middle OCs, and this was partly explained by work-related SARS-CoV-2 exposures. Conclusions Different socio-occupational patterns of symptoms were observed in the two groups of regions. The situation in the less affected regions, with more reporting in the highest relative to the lowest classes, may be attributable to exposure factors playing a role opposite to that of work-related exposures. Further studies on OC disparities in COVID-19 severity are needed based on hospitalization and mortality. Key messages • During the early pandemic, in regions less affected by COVID-19, the upper occupational class reported more COVID-19 symptoms, whereas the middle class did so in highly affected regions. • Work-related exposure to SARS-CoV-2 mediates the association between occupational class and reporting COVID-19 symptoms to some extent, even when the occupational gradient is reversed.

Emergency department nurses' reflective thinking and patient safety competency: The mediating effect of patient safety culture

AimThis study aimed to identify the mediating effect of patient safety culture on the relationship between reflective thinking and patient safety competency in emergency department nurses. BackgroundGiven the complexity and the need for timely assessments and interventions in the emergency department, the patient safety competency of nurses is crucial for preventing safety incidents. MethodsThis study utilized a cross-sectional descriptive correlational design with a convenience sample of 200 emergency department nurses. Participants completed a web-based, self-administered questionnaire that assessed reflective thinking, patient safety culture, and patient safety competency. The percentile bootstrap method for mediation analysis was performed to ascertain the mediating role of patient safety culture in the relationship between reflective thinking and patient safety competency. ResultsBoth reflective thinking and patient safety culture were significant predictors of patient safety competency. Furthermore, patient safety culture was found to mediate the relationship between reflective thinking and patient safety competency among emergency department nurses. ConclusionsThe findings suggest that emergency department nurses could benefit from a competency enhancement program or quality improvement projects that focus on reflective thinking and patient safety culture, which are significant predictors of patient safety competency.

Mediation analysis in longitudinal study with high-dimensional methylation mediators.

Mediation analysis has been widely utilized to identify potential pathways connecting exposures and outcomes. However, there remains a lack of analytical methods for high-dimensional mediation analysis in longitudinal data. To tackle this concern, we proposed an effective and novel approach with variable selection and the indirect effect (IE) assessment based on both linear mixed-effect model and generalized estimating equation. Initially, we employ sure independence screening to reduce the dimension of candidate mediators. Subsequently, we implement the Sobel test with the Bonferroni correction for IE hypothesis testing. Through extensive simulation studies, we demonstrate the performance of our proposed procedure with a higher F$_{1}$ score (0.8056 and 0.9983 at sample sizes of 150 and 500, respectively) compared with the linear method (0.7779 and 0.9642 at the same sample sizes), along with more accurate parameter estimation and a significantly lower false discovery rate. Moreover, we apply our methodology to explore the mediation mechanisms involving over 730 000 DNA methylation sites with potential effects between the paternal body mass index (BMI) and offspring growing BMI in the Shanghai sleeping birth cohort data, leading to the identification of two previously undiscovered mediating CpG sites.

Pengaruh Citra Merek dan Kualitas Produk terhadap Minat Beli Baju Thrifthing Dimediasi Kepercayaan dan Sikap Konsumen dalam Perspektif Bisnis Islam

The development of trade has provided very free space for movement in every transaction so that goods and services are easily owned and consumed by consumers, one of which is thrifting clothing which is one of the most basic needs for humans which is very important to use to cover and protect the body in every his activities. The aim of this research is to analyze the influence of brand image on consumer trust, the influence of product quality on consumer trust, the mediating role of consumer trust on the relationship between brand image and product quality, the mediating role of consumer attitudes on the relationship between brand image and product quality, the influence of brand image on buying interest, and the influence of product quality on purchasing interest. The influence of brand image and product quality on interest in buying thrift clothes in the growing fashion industry. This research also examines the mediating role of consumer beliefs and attitudes in the Islamic business perspective. By using regression and mediation analysis methods, the results of this research can provide valuable insight for business people, especially in understanding the preferences and behavior of Muslim consumers who are increasingly consuming fashion products. The research results conclude that the relationship between brand image has a positive and significant effect on consumer trust. , The relationship between product quality has a positive and significant effect on consumer trust, The mediating role of consumer trust strengthens the relationship between brand image and product quality, The mediating role of consumer attitude strengthens the relationship between brand image and product quality, The relationship between brand image has a positive and significant effect on purchase intention, and The relationship between product quality has a positive and significant effect on purchasing interest.

Consumers' Psychology Regarding Attachment to Social Media and Usage Frequency: A Mediated-Moderated Model.

Although there are studies in the literature investigating the effect of social media marketing activities (SMMAs) on brand equity and purchase intentions, scant information is available regarding consumers' attachment to social media (ASM) and usage frequency considering the abovementioned variables. Accordingly, one of the main purposes of this study is to investigate the effect of consumers' ASM on their perceptions of SMMAs. The second main purpose of this study is to test whether social media usage frequency has a moderating effect regarding the impact of perceived SMMAs on brand equity and purchase intentions. Questionnaires were collected face-to-face and a data set of 907 Turkish youth consumers were evaluated. Two major international technology brands were selected for the purposes of this study. Hypotheses were tested using structural equation modeling and the bootstrapping method for mediation analysis. The results showed that ASM and social media usage frequency are distinctive factors in the context of perceived SMMAs. Consumers' ASM creates a psychological difference that positively affects their perceptions of brands' SMMAs. Moreover, social media usage frequency negatively moderates the effect of perceived SMMAs on brand equity and purchase intentions. Another important finding is that brand equity partially mediates the impact of perceived SMMAs on purchase intentions. The present article describes the first study to test the effect of consumers' ASM on perceived SMMAs and to investigate the moderating effect of social media usage frequency regarding the effect of perceived SMMAs on brand equity and purchase intentions. The conceptual framework contains both a mediator and moderator that generated additional insights into the literature regarding the context of this study.

Contract governance to reduce antimicrobial overuse in hog farms in China

Antimicrobial resistance caused by the overuse of antimicrobials by farmers is an essential health issue. Currently, signing contracts between farmers and cooperatives has become crucial for small farmers to integrate into the modern agricultural industry chain. Unlike vertical government governance, which aims to intervene in the overuse of antimicrobials by farmers through many mandatory or incentive measures, contract governance refers to the social governance model that clarifies rights and obligations between farmers and cooperatives to ensure the adequate performance of contracts, which is especially beneficial to regulate farmers' safe production behavior such as the standard use of antimicrobials. However, there is a research gap concerning the effectiveness of contract governance in inhibiting farmers' overuse of animal antimicrobials. This study applies propensity score matching and mediation analysis method to assess how contract governance affects the overuse of antimicrobials by hog farmers. The paper uses data from 498 hog farmers of China's Hebei, Henan, and Hubei provinces to explore the impact and underlying mechanisms of contract governance on antimicrobial overuse in agriculture. The results showed that contract governance was found to inhibit the overuse of antimicrobials, with the amount paid for antimicrobials reduced by 118 yuan/household. We found evidence that this effect is exerted through three mechanisms: cooperative supervision (CS), technical guidance (TG), and product premium perception (PP). The CS, TG, and PP mediation effects accounted for 19.94%, 27.90%, and 26.93% of the total impact, respectively. Therefore, policy implications of these results include strengthening the standard of contract signing procedures and the integrity of executing contracts, increasing the market premium for products that meet the antimicrobial residue standards, and enhancing farmers' knowledge and contracting ability.

Causal inference with hidden mediators

Summary Proximal causal inference was recently proposed as a framework to identify causal effects from observational data in the presence of hidden confounders for which proxies are available. In this paper, we extend the proximal causal inference approach to settings where identification of causal effects hinges upon a set of mediators that are not observed, yet error prone proxies of the hidden mediators are measured. Specifically, (i) we establish causal hidden mediation analysis, which extends classical causal mediation analysis methods for identifying natural direct and indirect effects under no unmeasured confounding to a setting where the mediator of interest is hidden, but proxies of it are available; (ii) we establish a hidden front-door criterion, criterion to allow for hidden mediators for which proxies are available; (iii) we show that the identification of a certain causal effect called the population intervention indirect effect remains possible with hidden mediators in settings where challenges in (i) and (ii) might co-exist. We view (i)–(iii) as important steps towards the practical application of front-door criteria and mediation analysis as mediators are almost always measured with error and, thus, the most one can hope for in practice is that the measurements are at best proxies of mediating mechanisms. We propose identification approaches for the parameters of interest in our considered models. For the estimation aspect, we propose an influence function-based estimation method and provide an analysis for the robustness of the estimators.

Mediating pathways between neighborhood disadvantage and cardiovascular risk: Quasi-experimental evidence from a Danish refugee dispersal policy.

Research has documented that neighborhood disadvantage is associated with increased cardiovascular disease risk, but it is unclear which mechanistic pathways mediate this association across the life course. Leveraging a natural experiment in which refugees to Denmark were quasi-randomly assigned to neighborhoods across the country during 1986-1998 and using 30 years of follow-up data from population and health registers, we assessed whether and how individual-level poverty, unstable employment, and poor mental health mediate the relation between neighborhood disadvantage and the risk of hypertension, hyperlipidemia, and type 2 diabetes among Danish refugees (N= 40,811). Linear probability models using the discrete time-survival framework showed that neighborhood disadvantage was associated with increased risk of hypertension (0.05 percentage points [pp] per year [95%CI -0.00, 0.10]); hyperlipidemia (0.03 pp per year [95%CI -0.01, 0.07]), and diabetes (0.01 pp per year (95%CI -0.02, 0.03)). The Baron-Kenny product-of-coefficients method for counterfactual mediation analysis indicated that cumulative income mediated 6%-28% of the disadvantage effect on these outcomes. We find limited evidence of mediation by unstable employment and poor mental health. This study informs our theoretical understanding of the pathways linking neighborhood disadvantage with cardiovascular disease risk and identifies income security as a promising point of intervention in future research.

A Bayesian high-dimensional mediation analysis for multilevel genome-wide epigenetic data

Causal mediation analysis has increasingly become a popular practice in various clinical trials and epidemiological applications to evaluate whether an intermediate variable is on the pathway between the exposure of interest and a response. Previous mediation analyses in the literature mainly focused on settings with a single or low-dimensional mediators and single-level data. In this article, we propose a Bayesian causal mediation analysis method that can handle our multilevel intergenerational epigenetic mechanisms study (IEMS) with high-dimensional mediators. Specifically, we develop a Bayesian hierarchical model for data with such complexity, and then employ the Bayesian spike-and-slab priors on the exposure-mediator-outcome effect pathway to identify active mediators involved in mediation. We derive the natural indirect and direct effects based on our hierarchical model and provide statistical inference based on Markov chain Monte Carlo (MCMC) methods. Our simulation study demonstrates that our proposed Bayesian method outperforms other alternative methods in various scenarios. We further illustrate the utility of our method to IEMS to assess the causal mechanisms between maternal exposure to climate extremes and offspring's growth outcomes through DNA methylation.

Causal Mediation Analysis with the Parallel Process Latent Growth Curve Mediation Model

In parallel process latent growth curve mediation models, the mediation pathways from treatment to the intercept or slope of outcome through the intercept or slope of mediator are often of interest. In this study, we developed causal mediation analysis methods for these mediation pathways. Particularly, we provided causal definitions and identification results for the interventional indirect effects via the mediator intercept (or slope) alone and due to their mutual dependence. For estimation, we proposed an interaction model that incorporates interactions among the mediator intercept/slope and treatment, coupled with a Bayesian method. We evaluated the studied methods through simulations, and illustrated their applications using an empirical example.

The impact of remote work arrangements on freight forwarders job performance, satisfaction, and motivation

Remote work arrangements have become a critical argument both for employees and employers, particularly during the COVID-19 coronavirus crisis. The continuity of remote work arrangements has come into question as the pandemic disease diminished. Several industries and companies have recognized the advantages of remote work and made remote or flexible work a permanent part of their operations. Additionally, certain employees, perceiving the more favorable conditions provided by remote work, have refused to return to the office or have requested permanent remote work arrangements. Still, many employers are still questioning the pros and cons of remote work. In this context, this research focuses on freight forwarder employees who are assumed to be adaptable to work remotely due to the nature of their work. The research aims to determine current working arrangements and the effect of working remotely on the productivity, satisfaction, and motivation of freight forwarders. Data on these variables were collected through an online survey. All participants were individuals working for private companies in the freight forwarding industry. In an effort to minimize cultural impacts, companies located in Turkey have been chosen as the main sampling in the study. Through statistical analysis, the impact and factors influencing remote work arrangements on employee performance are explored. The effects and relationships between job performance, job motivation, job satisfaction, and work arrangement were examined by regression, correlation, and mediation analysis methods. Revealed findings present significant results for employers aiming to measure the effectiveness of remote work practices and policies.

The association between telomere length and blood lipids: a bidirectional two-sample Mendelian randomization study.

Observational studies suggest an association between telomere length (TL) and blood lipid (BL) levels. Nevertheless, the causal connections between these two traits remain unclear. We aimed to elucidate whether genetically predicted TL is associated with BL levels via Mendelian randomization (MR) and vice versa. We obtained genetic instruments associated with TL, triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), apolipoprotein A-1 (ApoA-1) and apolipoprotein B (ApoB) from large-scale genome-wide association studies (GWASs). The causal relationships between TL and BL were investigated via bidirectional MR, multivariable MR and mediation analysis methods. The inverse variance weighted (IVW) method was employed as the principal methodology, complemented by several other estimators to enhance the robustness of the analysis. In the forward MR analyses, we identified significant positive correlation between genetically predicted TL and the levels of TG (β=0.04, 95% confidence interval [CI]: 0.01 to 0.06, p = 0.003). In the reverse MR analysis, TG (β=0.02, 95% CI: 0.01 to 0.03, p = 0.004), LDL-C (β=0.03, 95% CI: 0.01 to 0.04, p = 0.001) and ApoB (β=0.03, 95% CI: 0.01 to 0.04, p = 9.71×10-5) were significantly positively associated with TL, although this relationship was not observed in the multivariate MR analysis. The mediation analysis via two-step MR showed no significant mediation effects acting through obesity-related phenotypes in analysis of TL with TG, while the effect of LDL-C on TL was partially mediated by body mass index (BMI) in the reverse direction, with mediated proportion of 12.83% (95% CI: 0.62% to 25.04%). Our study indicated that longer TL were associated with higher TG levels, while conversely, higher TG, LDL-C, and ApoB levels predicted longer TL, with BMI partially mediating these effects. Our findings present valuable insights into the development of preventive strategies and interventions that specifically target TL-related aging and age-related diseases.

Causal mediation analysis with a three-dimensional image mediator.

Causal mediation analysis is increasingly abundant in biology, psychology, and epidemiology studies and so forth. In particular, with the advent of the big data era, the issue of high-dimensional mediators is becoming more prevalent. In neuroscience, with the widespread application of magnetic resonance technology in the field of brain imaging, studies on image being a mediator emerged. In this study, a novel causal mediation analysis method with a three-dimensional image mediator is proposed. We define the average casual effects under the potential outcome framework, explore several sufficient conditions for the valid identification, and develop techniques for estimation and inference. To verify the effectiveness of the proposed method, a series of simulations under various scenarios is performed. Finally, the proposed method is applied to a study on the causal effect of mother's delivery mode on child's IQ development. It is found that cesarean section may have a negative effect on intellectual performance and that this effect is mediated by white matter development. Additional prospective and longitudinal studies may be necessary to validate these emerging findings.

The Impact of Technological Innovation on Agricultural Green Total Factor Productivity: The Mediating Role of Environmental Regulation in China

This study delves into the effects of agricultural technological innovation on agricultural green total factor productivity (AGTFP) and the intermediating role of environmental regulation (ER) in 30 Chinese provinces from 2010 to 2021. Employing mediation analysis methods such as the three-step approach, Sobel–Goodman test, and Bootstrap methods, the findings are robust: technological innovation significantly enhances AGTFP, as evidenced by a 1% level significant coefficient of 0.030. Additionally, ER acts as a potent mediator, where its inclusion as an independent variable alongside agricultural technological innovation (AST) boosts the coefficient to 0.031, further confirming its synergistic effect on AGTFP. These data points underline the importance of innovation in agricultural sustainability and the reinforcing role of environmental regulation. Consequently, this study advocates for intensified agricultural innovation support, tailored environmental regulation policies, augmented environmental education, and a meticulous evaluation system for environmental legislation to foster sustainable agricultural practices.

Bayesian Mediation Analysis with an Application to Explore Racial Disparities in the Diagnostic Age of Breast Cancer

A mediation effect refers to the effect transmitted by a mediator intervening in the relationship between an exposure variable and a response variable. Mediation analysis is widely used to identify significant mediators and to make inferences on their effects. The Bayesian method allows researchers to incorporate prior information from previous knowledge into the analysis, deal with the hierarchical structure of variables, and estimate the quantities of interest from the posterior distributions. This paper proposes three Bayesian mediation analysis methods to make inferences on mediation effects. Our proposed methods are the following: (1) the function of coefficients method; (2) the product of partial difference method; and (3) the re-sampling method. We apply these three methods to explore racial disparities in the diagnostic age of breast cancer patients in Louisiana. We found that African American (AA) patients are diagnosed at an average of 4.37 years younger compared with Caucasian (CA) patients (57.40 versus 61.77, p&lt; 0.0001). We also found that the racial disparity can be explained by patients’ insurance (12.90%), marital status (17.17%), cancer stage (3.27%), and residential environmental factors, including the percent of the population under age 18 (3.07%) and the environmental factor of intersection density (9.02%).

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).

Partner’s unemployment and subjective well-being: The mediating role of relationship functioning

Unemployment affects not only the subjective well-being of the individual, but also that of the partner. Based on the life course perspective and the spillover-crossover-model, we examine the mediating role of relationship functioning for such crossover effects of partner’s unemployment on subjective well-being. We also test whether gender differences in the mechanism of relationship functioning can explain the larger overall crossover effects on women compared to men. We use data from the German Family Panel pairfam (2008/09–2018/19), which provide more direct and comprehensive measures of relationship functioning than previous research, and allow us to examine couples’ communication and interactions, their conflict styles and behaviors, relationship satisfaction, and perceived relationship instability as mediators. To analyze the impact of the partner’s transition to unemployment on subjective well-being, we use fixed effects panel regression models and the product method of mediation analysis to estimate the indirect effects of relationship functioning. The results show that a partner’s transition to unemployment has a negative impact on one’s own well-being. The effects are more pronounced for women than men which can be partly explained by gender-specific effects of the partner’s unemployment on various aspects of relationship functioning, rather than by differential effects of the latter on one’s own well-being.

Methods for the Analysis of Multiple Epigenomic Mediators in Environmental Epidemiology.

Epigenetic changes can be highly influenced by environmental factors and have in turn been proposed to influence chronic disease. Being able to quantify to which extent epigenomic processes are mediators of the association between environmental exposures and diseases is of interest for epidemiologic research. In this review, we summarize the proposed mediation analysis methods with applications to epigenomic data. The ultra-high dimensionality and high correlations that characterize omics data have hindered the precise quantification of mediated effects. Several methods have been proposed to deal with mediation in high-dimensional settings, including methods that incorporate dimensionality reduction techniques to the mediation algorithm. Although important methodological advances have been conducted in the previous years, key challenges such as the development of sensitivity analyses, dealing with mediator-mediator interactions, including environmental mixtures as exposures, or the integration of different omic data should be the focus of future methodological developments for epigenomic mediation analysis.