Does exercise adherence during the COVID-19 pandemic contribute to improved subjective well-being? A cross-sectional study.

Introduction: This study aims to investigate whether exercise adherence and positive mental character significantly affect subjective well-being among Chinese college students during the COVID-19 pandemic and whether positive mental character plays a mediating role. Methods: The study employed questionnaires, including the Exercise Adherence Scale, the Positive Mental Character Scale, and the Subjective Well-Being Scale, which were administered to students across seven universities in Henan Province, China. A total of 1,001 participants were analyzed in the final sample. Data were analyzed using SPSS 21.0 for descriptive statistics, independent samples T-test, correlation, and regression analyses. Furthermore, structural equation model with AMOS was conducted to examine the potential mediating effect of positive mental characteristics on the relationship between exercise adherence and subjective well-being. Results: The results indicated significant differences in exercise adherence, positive mental character, and subjective well-being between male and female participants, with males scoring higher in all three domains. Among Chinese university students during the COVID-19 pandemic, there was a significant correlation among exercise adherence, positive mental character, and subjective well-being. Exercise adherence was found to have a significant and positive impact on both positive mental character and subjective well-being. Additionally, it was found that positive mental character had a significant positive association with subjective well-being. The mediating role of positive mental character in the relationship between exercise adherence and subjective well-being was partially supported. Discussion: Exercise adherence among Chinese college students had a significant positive association on both positive mental character and subjective well-being throughout the COVID-19 pandemic. The exercise adherence can directly or indirectly enhance subjective well-being through its association with positive mental character. Therefore, positive mental and subjective well-being can be enhanced by consistent physical activity even during a pandemic.

Benchmark Dose of Melamine Exposure for a Renal Injury Marker Mediated by Oxidative Stress: Examples in Patients with Urolithiasis and Occupational Workers.

Establishing a safe exposure level from epidemiological studies while providing direct hazard characterization in humans often faces uncertainty in causality, especially cross-sectional data. With advances in molecular epidemiology, it is reasonable to integrate identified intermediate biomarkers into health risk assessment. In this study, by considering the mediation of the oxidative stress marker malondialdehyde (MDA), we explored the exposure threshold of melamine on the early renal injury marker N-acetyl-ß-D glucosaminidase (NAG). The benchmark dose (BMD) was derived from model averaging of the composite direct effect of melamine exposure and the indirect effect through the mediation of MDA on NAG levels. As illustrative examples, we analyzed 309 adult patients with calcium urolithiasis and 80 occupational workers for the corresponding exposure thresholds. The derived threshold was subpopulation-dependent, with the one-sided lower bound BMDL10 for the patients with urolithiasis with (without) the mediator MDA for the patients with kidney stones and the occupational workers being 0.88 (0.96) µg/kg_bw/day and 22.82 (18.09) µg/kg_bw/day, respectively. The derived threshold levels, considering the oxidative stress marker MDA, were consistent with those without adjusting for the mediation effect. However, the study outcomes were further supported by the suggested mechanism pathway. The threshold for the patients with urolithiasis was up to two orders lower than the current tolerable daily intake level of 200 µg/kg_bw/day recommended by the WHO (EFSA).

Detecting Nonadditive Biotic Interactions and Assessing Their Biological Relevance among Temperate Rainforest Trees.

AbstractInteractions between and within abiotic and biotic processes generate nonadditive density-dependent effects on species performance that can vary in strength or direction across environments. If ignored, nonadditivities can lead to inaccurate predictions of species responses to environmental and compositional changes. While there are increasing empirical efforts to test the constancy of pairwise biotic interactions along environmental and compositional gradients, few assess both simultaneously. Using a nationwide forest inventory that spans broad ambient temperature and moisture gradients throughout New Zealand, we address this gap by analyzing the diameter growth of six focal tree species as a function of neighbor densities and climate, as well as neighbor × climate and neighbor × neighbor statistical interactions. The most complex model featuring all interaction terms had the highest predictive accuracy. Compared with climate variables, biotic interactions typically had stronger effects on diameter growth, especially when subjected to nonadditivities from local climatic conditions and the density of intermediary species. Furthermore, statistically strong (or weak) nonadditivities could be biologically irrelevant (or significant) depending on whether a species pair typically interacted under average or more extreme conditions. Our study highlights the importance of considering both the statistical potential and the biological relevance of nonadditive biotic interactions when assessing species performance under global change.

Decomposing the association of psychosocial wellbeing with all-cause mortality: the mediating role of physical health and lifestyle factors.

PURPOSE: This study quantified the effect of 48 psychosocial constructs on all-cause mortality using data from 7,698 individuals in the U.S. Health and Retirement Study. METHODS: Latent class analysis was used to divide participants into mutually exclusive psychosocial wellbeing groups (good, average, or poor) which was subsequently considered as the exposure. Mediation analysis was then conducted to determine the direct effect of the psychosocial wellbeing groups and the indirect (mediating) effects of physical health (functional status and comorbid conditions) and lifestyle factors (physical activity, smoking, and alcohol consumption) on overall survival. We also created a composite health index measure representing the summative effect of the mediators. RESULTS: We observed a strong and statistically significant total effect (TE) between survival time and psychosocial wellbeing group (survival time ratio (SR) = 1.73, 95% confidence interval (CI):1.50,2.01 when comparing good to poor). Mediation analysis revealed that the direct effect via psychosocial wellbeing group accounted for more than half of the TE (SR = 1.46, 95% CI:1.27,1.67). The composite health index measure mediated 36.2% of the TE with the natural indirect effect SR of 1.18 (95% CI:1.13,1.22). CONCLUSION: Our findings demonstrate the interconnectedness between psychosocial wellbeing and physical health and lifestyle factors on survival.

Simulation of Radiation-Induced DNA Damage and Protection by Histones Using the Code RITRACKS.

(1) Background: DNA damage is of great importance in the understanding of the effects of ionizing radiation. Various types of DNA damage can result from exposure to ionizing radiation, with clustered types considered the most important for radiobiological effects. (2) Methods: The code RITRACKS (Relativistic Ion Tracks), a program that simulates stochastic radiation track structures, was used to simulate DNA damage by photons and ions spanning a broad range of linear energy transfer (LET) values. To perform these simulations, the transport code was modified to include cross sections for the interactions of ions or electrons with DNA and amino acids for ionizations, dissociative electron attachment, and elastic collisions. The radiochemistry simulations were performed using a step-by-step algorithm that follows the evolution of all particles in time, including reactions between radicals and DNA structures and amino acids. Furthermore, detailed DNA damage events, such as base pair positions, DNA fragment lengths, and fragment yields, were recorded. (3) Results: We report simulation results using photons and the ions 1H+, 4He2+, 12C6+, 16O8+, and 56Fe26+ at various energies, covering LET values from 0.3 to 164 keV/µm, and performed a comparison with other codes and experimental results. The results show evidence of DNA protection from damage at its points of contacts with histone proteins. (4) Conclusions: RITRACKS can provide a framework for studying DNA damage from a variety of ionizing radiation sources with detailed representations of DNA at the atomic scale, DNA-associated proteins, and resulting DNA damage events and statistics, enabling a broader range of future comparisons with experiments such as those based on DNA sequencing.

Unraveling emergent network indeterminacy in complex ecosystems: A random matrix approach.

Indeterminacy of ecological networks-the unpredictability of ecosystem responses to persistent perturbations-is an emergent property of indirect effects a species has on another through interaction chains. Thus, numerous indirect pathways in large, complex ecological communities could make forecasting the long-term outcomes of environmental changes challenging. However, a comprehensive understanding of ecological structures causing indeterminacy has not yet been reached. Here, using random matrix theory (RMT), we provide mathematical criteria determining whether network indeterminacy emerges across various ecological communities. Our analytical and simulation results show that indeterminacy intricately depends on the characteristics of species interaction. Specifically, contrary to conventional wisdom, network indeterminacy is unlikely to emerge in large competitive and mutualistic communities, while it is a common feature in top-down regulated food webs. Furthermore, we found that predictable and unpredictable perturbations can coexist in the same community and that indeterminate responses to environmental changes arise more frequently in networks where predator-prey relationships predominate than competitive and mutualistic ones. These findings highlight the importance of elucidating direct species relationships and analyzing them with an RMT perspective on two fronts: It aids in 1) determining whether the network's responses to environmental changes are ultimately indeterminate and 2) identifying the types of perturbations causing less predictable outcomes in a complex ecosystem. In addition, our framework should apply to the inverse problem of network identification, i.e., determining whether observed responses to sustained perturbations can reconstruct their proximate causalities, potentially impacting other fields such as microbial and medical sciences.

Bioreactor Expansion Affects Microbial Succession of Mixotrophic Acidophiles and Bioremediation of Cadmium-Contaminated Soils.

Microbial scale-up cultivation is the first step to bioremediating cadmium (Cd)-contaminated soils at the industrial scale. However, the changes in the microbial community as the bioreactor volume expands and their associations with soil Cd removal remain unclear. Herein, a six-stage scale-up cultivation process of mixotrophic acidophiles was conducted, scaling from 0.1 L to 10 m3, to remediate Cd-contaminated soils. The findings showed that bioreactor expansion led to a delay in sulfur and glucose oxidations, resulting in a reduced decline in solution pH and cell density. There were minimal differences observed in bacterial alpha-diversity and community structure as the bioreactor volume increased, except for the 10 m3 scale. However, bioreactor expansion decreased fungal alpha-diversity, changed the community structure, and simplified fungal community compositions. At the family level, Acidithiobacillaceae and Debaryomycetaceae dominated the bacterial and fungal communities throughout the scale-up process, respectively. Correlation analysis indicated that the indirect effect of mixotrophic acidophiles played a significant role in soil Cd removal. Bacterial community shifts, driven by changes in bioreactor volume, decreased the pH value through sulfur oxidation, thereby indirectly enhancing Cd removal efficiency. This study will contribute to the potential industrial application of mixotrophic acidophiles in bioremediating Cd-contaminated soils.

Indirect effects in mediation analyses should not be tested for statistical significance.

BACKGROUND AND OBJECTIVE: Mediation analysis is used to gain insight into the mechanisms of exposure-outcome effects by dividing this effect into a direct and an indirect effect. One of the problems of mediation analysis is that in many situations, the standard error of the indirect effect is much lower than the standard errors of the total and direct effect. Because this problem is ignored in the epidemiological literature, the purpose of this paper was to illustrate this problem and to provide an advice regarding the statistical testing of indirect effects in mediation analysis. METHODS: To illustrate the problem of the estimation of the standard error of the indirect effect two real life datasets and several simulations are used. RESULTS: The paper shows that the problem of estimating the standard error of the indirect effect was most pronounced when the relationship between exposure and mediator and the relationship between mediator and outcome were equally strong. Furthermore, the magnitude of the estimation problem is different for different strengths of the mediation effect. CONCLUSION: The indirect effect in mediation analysis should not be tested for statistical significance but the importance of mediation should be evaluated by its clinical relevance.

Signal-to-Noise Ratio in Estimating and Testing the Mediation Effect: Structural Equation Modeling versus Path Analysis with Weighted Composites.

Mediation analysis plays an important role in understanding causal processes in social and behavioral sciences. While path analysis with composite scores was criticized to yield biased parameter estimates when variables contain measurement errors, recent literature has pointed out that the population values of parameters of latent-variable models are determined by the subjectively assigned scales of the latent variables. Thus, conclusions in existing studies comparing structural equation modeling (SEM) and path analysis with weighted composites (PAWC) on the accuracy and precision of the estimates of the indirect effect in mediation analysis have little validity. Instead of comparing the size on estimates of the indirect effect between SEM and PAWC, this article compares parameter estimates by signal-to-noise ratio (SNR), which does not depend on the metrics of the latent variables once the anchors of the latent variables are determined. Results show that PAWC yields greater SNR than SEM in estimating and testing the indirect effect even when measurement errors exist. In particular, path analysis via factor scores almost always yields greater SNRs than SEM. Mediation analysis with equally weighted composites (EWCs) also more likely yields greater SNRs than SEM. Consequently, PAWC is statistically more efficient and more powerful than SEM in conducting mediation analysis in empirical research. The article also further studies conditions that cause SEM to have smaller SNRs, and results indicate that the advantage of PAWC becomes more obvious when there is a strong relationship between the predictor and the mediator, whereas the size of the prediction error in the mediator adversely affects the performance of the PAWC methodology. Results of a real-data example also support the conclusions.

Lipids as potential mediators linking body mass index to diabetes: evidence from a mediation analysis based on the NAGALA cohort.

BACKGROUND: Body mass index (BMI) and lipid disorders are both known to be strongly associated with the development of diabetes, however, the indirect effect of lipid parameters in the BMI-related diabetes risk is currently unknown. This study aimed to investigate the mediating role of lipid parameters in the association of BMI with diabetes risk. METHODS: We assessed the association of diabetes risk with BMI, as well as lipid parameters including high-density lipoprotein cholesterol(HDL-C), low-density lipoprotein cholesterol(LDL-CF and LDL-CS), triglycerides(TG), total cholesterol(TC), remnant cholesterol(RC), non-HDL-C, and combined indices of lipid parameters with HDL-C (RC/HDL-C ratio, TG/HDL-C ratio, TC/HDL-C ratio, non-HDL/HDL-C ratio, LDL/HDL-C ratio) using data from 15,453 subjects in the NAGALA project. Mediation models were used to explore the mediating role of lipid parameters in the association of BMI with diabetes risk, and mediation percentages were calculated for quantifying the strength of the indirect effects. Finally, receiver operating characteristic curve (ROC) analysis was used to compare the accuracy of BMI and BMI combined with lipid parameters in predicting incident diabetes. RESULTS: Multivariate regression models, adjusted for confounding factors, demonstrated robust associations of lipid parameters, BMI, with diabetes risk, with the exception of TC, LDL-CF, LDL-CS, and non-HDL-C. Mediation analysis showed that lipid parameters except TC, LDL-CF, LDL-CS, and Non-HDL-C were involved in and mediated the association of BMI with diabetes risk, with the largest mediation percentage being the RC/HDL-C ratio, which was as high as 40%; it is worth mentioning that HDL-C and HDL-C-related lipid ratio parameters also play an important mediating role in the association between BMI and diabetes, with the mediator proportion being greater than 30%. Finally, based on the ROC results, we found that the prediction performance of all lipid parameters in the current study except TC was significantly improved when combined with BMI. CONCLUSION: Our fresh findings suggested that lipid parameters partially mediated the association of BMI with diabetes risk; this result indicated that in the context of diabetes risk screening and disease management, it is important to not only monitor BMI but also pay attention to lipid parameters, particularly HDL-C and HDL-C-related lipid ratio parameters.

The Indirect Effect of Sleep Quality on Stress-Related Psychosocial Outcomes in Adolescents: An Investigation Across Genders.

Sleep is foundational for adolescent psychosocial outcomes though often compromised by normative developmental changes and external factors. This cross-sectional study examined sleep quality as a mechanism linking stress and psychosocial outcomes and explored gender differences. Adolescents (N = 246; Mage=15.8; 46.3% female) completed self-report measures assessing sleep quality and psychosocial outcomes. Structural equation modeling results indicated sleep quality accounted for 78.4% of the total effect of stress on school functioning (b=-0.45, p < 0.001) and 54.2% of the total effect of stress on pain (b = 0.14, p = 0.002). A larger indirect effect of sleep quality on school functioning (b=-0.26, p = 0.016) emerged for boys than girls, and the effect of sleep quality on pain was significant only for girls (b = 0.18, p < 0.001, 69.6% of total effect). Sleep quality explained a large proportion of the effect of stress on school functioning and pain. Sleep quality represents a modifiable transdiagnostic pathway that may buffer the effects of stress in adolescence.

Insomnia and creativity in Chinese adolescents: mediation through need for cognition.

BACKGROUND: Creativity is an essential cognitive ability that plays a crucial role in advanced thinking. While previous research has demonstrated the impact of insomnia on cognitive function, its effects on creativity in Chinese adolescents remain unclear. This study explored the relationship between insomnia (specifically, daytime and nighttime disturbances) and creativity in adolescents. Additionally, it examined the potential mediating effect of the need for cognition on this relationship. METHODS: Questionnaires were administered to 302 adolescents to measure their creativity, need for cognition, and insomnia levels using the Williams Creative Tendencies Scale, Need for Cognition Scale, and Bergen Insomnia Scale, respectively. Regression analysis was conducted to examine the direct impact of insomnia on creativity. Furthermore, a mediation model was constructed to investigate the role of the need for cognition in mediating the relationship between insomnia and creativity. RESULTS: The findings of the present study indicated that insomnia had a direct impact on the creativity of adolescents, demonstrating a time-of-day effect. Daytime disturbances were found to have a positive correlation with overall creativity and imagination, whereas no significant direct effect was found between nighttime disturbances and creativity. Further analysis revealed that insomnia, specifically daytime disturbances, might influence creativity by affecting the individual's need for cognition. However, no similar indirect effects were observed for the relationship between nighttime disturbances and creativity. CONCLUSIONS: Our findings indicate that adolescents might experience improved creativity as a result of daytime disruptions, and the level of need for cognition could play a crucial role in understanding the link between insomnia and creativity in adolescents.

Third variables in longitudinal research: Application of longitudinal mediation and moderation in school psychology.

Third variable models, such as mediation and moderation, can identify contextual factors that help explain the relation between two variables. Although used less frequently in school psychology research, longitudinal mediation, longitudinal moderation, and the integration of these two approaches can be used to describe the developmental changes in children's psychological and behavioral processes throughout the school years and beyond. This article provides conceptual descriptions of longitudinal mediation, longitudinal moderation, longitudinal moderated mediation, and longitudinal mediated moderation and demonstrates the use of these methods with a large sample of elementary students. Extensions of these methods and applied examples from the literature are also discussed. The Mplus syntax from our illustrated examples are provided for those interested in reproducing the analyses.

The effect of renewable energy on carbon emissions through globalization.

The sustainability of the environment debate cannot be addressed without considering the type of energy to use. The pace at which the world is industrializing, globalizing, and developing economically has prompted many researchers to investigate the kind of energy required to preserve the environment. In this regard, this study employs the mediation model to assess renewable energy's direct and indirect effects on carbon emissions through globalization. The data for the study is from 1990 to 2020. The study's findings showed that while renewable energy has no appreciable impact on trade openness, it directly and negatively affects carbon emissions. However, foreign direct investment has a direct and significant positive effect on carbon emissions, while trade openness has no significant effect. The indirect result revealed that renewable energy through foreign direct investment has a negative effect on carbon emissions; however, renewable energy through trade openness has a positive effect on carbon emissions. Policymakers are encouraged to restrict the trade sector to reduce the trading of high-emission technologies.

[Quantitative Assessment of the Impact of Climate Change on the Growing Season of Vegetation Gross Primary Productivity in the Middle and Lower Reaches of the Yangtze River].

Quantitatively determining the direct, indirect, and comprehensive effects of climatic factors on the growing season of the vegetation GPP (GPPGS) in the middle and lower reaches of the Yangtze River at the regional and vegetation type scales can provide a scientific basis for the management and restoration of regional vegetation resources under the background of global climate change. Using MODIS GPP data, meteorological data, and vegetation type data, combined with Theil-Sen Median trend analysis and the Mann-Kendall significance test, the spatiotemporal characteristics of the GPPGS in the middle and lower reaches of the Yangtze River were investigated at different temporal and spatial scales. Path analysis was used to further reveal the direct, indirect, and comprehensive effects of climate factors on GPPGS variation in different vegetation types. The results showed that:① from 2000 to 2021, the vegetation GPPGS in the middle and lower reaches of the Yangtze River showed a fluctuating upward trend, with a rising rate (in terms of C, same below) of 2.70 g·(m2·a)-1 (P<0.01). The GPPGS of different vegetation types all showed a significant upward trend (P<0.01), with shrubs having the highest upward rate of 3.31 g·(m2·a)-1 and cultivated vegetation having the lowest upward rate of 2.54 g·(m2·a)-1. ② The proportion of the area with an upward trend in GPPGS in the middle and lower reaches of the Yangtze River was 88.11%. The proportion of the area with an upward trend in GPPGS was greater than 84% for all different vegetation types, with shrubs (49.76%) and cultivated vegetation (44.36%) having significantly higher proportions of the area with an upward trend than that in other vegetation types. ③ The path analysis results showed that precipitation and the maximum temperature had a significant positive direct effect on vegetation GPPGS (P<0.05), whereas solar radiation had a non-significant positive effect (P ≥ 0.05). The indirect effects of maximum temperature, precipitation, and solar radiation on vegetation GPPGS were all non-significantly negative (P ≥ 0.05). Under the combined effects of direct and indirect influences, precipitation and maximum temperature had a non-significant positive effect on vegetation GPPGS (P ≥ 0.05), whereas solar radiation had a non-significant negative effect on vegetation GPPGS (P ≥ 0.05). Among different vegetation types, precipitation was the main climate factor affecting the changes in GPPGS of cultivated vegetation, whereas the maximum temperature was the main climate factor affecting the changes in GPPGS of coniferous forests, broad-leaved forests, shrubs, and grasslands. ④ The changes in vegetation GPPGS in the middle and lower reaches of the Yangtze River were mainly influenced by the direct effects of maximum temperature, precipitation, and solar radiation, with the direct effect of precipitation dominating 56.72% of the changes in GPPGS. The research results can provide a reference for quantifying the carbon sequestration potential of vegetation in the middle and lower reaches of the Yangtze River and formulating ecological restoration governance policies tailored to local conditions under the background of global climate change.

Using instrumental variables to address unmeasured confounding in causal mediation analysis.

Mediation analysis is a strategy for understanding the mechanisms by which interventions affect later outcomes. However, unobserved confounding concerns may be compounded in mediation analyses, as there may be unobserved exposure-outcome, exposure-mediator, and mediator-outcome confounders. Instrumental variables (IVs) are a popular identification strategy in the presence of unobserved confounding. However, in contrast to the rich literature on the use of IV methods to identify and estimate a total effect of a non-randomized exposure, there has been almost no research into using IV as an identification strategy to identify mediational indirect effects. In response, we define and nonparametrically identify novel estimands-double complier interventional direct and indirect effects-when 2, possibly related, IVs are available, one for the exposure and another for the mediator. We propose nonparametric, robust, efficient estimators for these effects and apply them to a housing voucher experiment.

Soil Microbes and Plant-Associated Microbes in Response to Radioactive Pollution May Indirectly Affect Plants and Insect Herbivores: Evidence for Indirect Field Effects from Chernobyl and Fukushima.

The biological impacts of the nuclear accidents in Chernobyl (1986) and Fukushima (2011) on wildlife have been studied in many organisms over decades, mainly from dosimetric perspectives based on laboratory experiments using indicator species. However, ecological perspectives are required to understand indirect field-specific effects among species, which are difficult to evaluate under dosimetric laboratory conditions. From the viewpoint that microbes play a fundamental role in ecosystem function as decomposers and symbionts for plants, we reviewed studies on microbes inhabiting soil and plants in Chernobyl and Fukushima in an attempt to find supporting evidence for indirect field-specific effects on plants and insect herbivores. Compositional changes in soil microbes associated with decreases in abundance and species diversity were reported, especially in heavily contaminated areas of both Chernobyl and Fukushima, which may accompany explosions of radioresistant species. In Chernobyl, the population size of soil microbes remained low for at least 20 years after the accident, and the abundance of plant-associated microbes, which are related to the growth and defense systems of plants, possibly decreased. These reported changes in microbes likely affect soil conditions and alter plant physiology. These microbe-mediated effects may then indirectly affect insect herbivores through food-mass-mediated, pollen-mediated, and metabolite-mediated interactions. Metabolite-mediated interactions may be a major pathway for ecological impacts at low pollution levels and could explain the decreases in insect herbivores in Fukushima. The present review highlights the importance of the indirect field effects of long-term low-dose radiation exposure under complex field circumstances.

Relationship of environmental exposure temperature and temperature extremes on sperm DNA fragmentation index in men with different BMI values and the indirect effect of DNA fragmentation index on semen parameters.

Prior studies have established a significant correlation between the DNA fragmentation index (DFI) and infertility. Additionally, certain investigations suggest that environmental exposure may serve as an etiological factor impacting semen quality. This study aimed to explore the impact of season, ambient temperature, and weather extremes on the DFI of sperm, along with other relevant parameters. Furthermore, it sought to assess how ambient temperature affects the DFI of sperm and other semen parameters in populations with varying BMI values. Additionally, the study analyzed the transient indirect effect of DFI on sperm parameters. This retrospective study analyzed semen samples from 11,877 men, selected based on female factor considerations, spanning from January 2016 to December 2021. Participants were grouped according to the season of semen collection. The results showed that samples collected in summer had a lower semen volume and sperm motility, while those collected in autumn had a lower DFI. We analyzed the exposure-response ratio between environmental exposure temperature and semen parameters using a generalized additive model. Results showed that the curve of the exposure-response relationship was U-shaped or inverted U-shaped; when the air temperature exposure was below the threshold, for each degree of temperature increase, the total sperm motility, sperm concentration, and progressive motility increased by 0.16 %, 0.29 × 10 (Levine, 1999)/ml and 0.14 %, respectively, while the DFI and inactivity rate decreased by 0.078 % and 0.15 %, respectively. When the air temperature exposure exceeded the threshold, for each degree of temperature increase, the sperm concentration, total sperm motility, semen volume and progressive motility decreased by 0.42 × 10 (Levine, 1999)/ml, 0.11 %, 0.0078 ml and 0.15 %, respectively, while the DFI and inactivity rate increased by 0.13 % and 0.12 %, respectively. Extremely cold weather during spermatogenesis was positively correlated with DFI, and extremely hot weather was negatively correlated with sperm motility. Subgroup analysis revealed that individuals classified as overweight / obese exhibited more pronounced changes in sperm parameters and the DFI in response to variations in environmental exposure temperature compared to those with a normal BMI. In the analysis of the relationship between DFI and sperm parameters, the results showed an inverted U-shape relationship between DFI and semen volume, and a negative correlation between DFI and sperm concentration and sperm motility. And we found that ambient temperature affects sperm parameters through DFI at low as well as average temperatures, whereas at high temperatures this indirect effect is no longer present.

Causal inference with a mediated proportional hazards regression model.

The natural direct and indirect effects in causal mediation analysis with survival data having one mediator is addressed by VanderWeele (2011) [1]. He derived an approach for (1) an accelerated failure time regression model in general cases and (2) a proportional hazards regression model when the time-to-event outcome is rare. If the outcome is not rare, then VanderWeele (2011) [1] did not derive a simple closed-form expression for the log-natural direct and log-natural indirect effects for the proportional hazards regression model because the baseline cumulative hazard function does not approach zero. We develop two approaches to extend VanderWeele's approach, in which the assumption of a rare outcome is not required. We obtain the natural direct and indirect effects for specific time points through numerical integration after we calculate the cumulative baseline hazard by (1) applying the Breslow method in the Cox proportional hazards regression model to estimate the unspecified cumulative baseline hazard; (2) assuming a piecewise constant baseline hazard model, yielding a parametric model, to estimate the baseline hazard and cumulative baseline hazard. We conduct simulation studies to compare our two approaches with other methods and illustrate our two approaches by applying them to data from the ASsessment, Serial Evaluation, and Subsequent Sequelae in Acute Kidney Injury (ASSESS-AKI) Consortium.