Effects Linear Regression Models Research Articles

Public greenspace and mental wellbeing among mid-older aged adults: Findings from the HABITAT longitudinal study

We explored temporal associations between public greenspace and adults’ mental wellbeing. Participants (n = 5,906) aged 40–65 years at baseline had data at >2 post-baseline waves of HABITAT, a multilevel longitudinal study (2007–16) in Brisbane, Australia. Participants self-reported mental wellbeing (short Warwick-Edinburgh Mental Wellbeing Scale) and neighbourhood self-selection reasons at Waves 2–5 (2009-11-13-16). We examined associations between Δgreenspace (within 1 km of home) and Δmental wellbeing using a linear fixed effects model, adjusting for time-varying confounders. Mental wellbeing increased (β = 1.75; 95% Confidence Interval:0.25–3.26) with greenspace exposure, adjusting for self-selection. Urban planning and policy initiatives to increase public greenspace may benefit mental wellbeing.

Meta-Analytic Gene-Clustering Algorithm for Integrating Multi-Omics and Multi-Study Data.

Gene pathways and gene-regulatory networks are used to describe the causal relationship between genes, based on biological experiments. However, many genes are still to be studied to define novel pathways. To address this, a gene-clustering algorithm has been used to group correlated genes together, based on the similarity of their gene expression level. The existing methods cluster genes based on only one type of omics data, which ignores the information from other types. A large sample size is required to achieve an accurate clustering structure for thousands of genes, which can be challenging due to the cost of multi-omics data. Meta-analysis has been used to aggregate the data from multiple studies and improve the analysis results. We propose a computationally efficient meta-analytic gene-clustering algorithm that combines multi-omics datasets from multiple studies, using the fixed effects linear models and a modified weighted correlation network analysis framework. The simulation study shows that the proposed method outperforms existing single omic-based clustering approaches when multi-omics data and/or multiple studies are available. A real data example demonstrates that our meta-analytic method outperforms single-study based methods.

Physiologic validation of the Compensatory Reserve Metric obtained from pulse oximetry: A step toward advanced medical monitoring on the battlefield.

The Compensatory Reserve Metric (CRM) provides a time sensitive indicator of hemodynamic decompensation. However, its in-field utility is limited because of the size and cost-intensive nature of standard vital sign monitors or photoplethysmographic volume-clamp (PPG VC ) devices used to measure arterial waveforms. In this regard, photoplethysmographic measurements obtained from pulse oximetry may serve as a useful, portable alternative. This study aimed to validate CRM values obtained using pulse oximeter (PPG PO ). Forty-nine healthy adults (25 females) underwent a graded lower body negative pressure (LBNP) protocol to simulate hemorrhage. Arterial waveforms were sampled using PPG PO and PPG VC . The CRM was calculated using a one-dimensional convolutional neural network. Cardiac output and stroke volume were measured using PPG VC . A brachial artery catheter was used to measure intra-arterial pressure. A three-lead electrocardiogram was used to measure heart rate. Fixed-effect linear mixed models with repeated measures were used to examine the association between CRM values and physiologic variables. Log-rank analyses were used to examine differences in shock determination during LBNP between monitored hemodynamic parameters. The median LBNP stage reached was 70 mm Hg (range, 45-100 mm Hg). Relative to baseline, at tolerance, there was a 47% ± 12% reduction in stroke volume, 64% ± 27% increase in heart rate, and 21% ± 7% reduction in systolic blood pressure ( p < 0.001 for all). Compensatory Reserve Metric values obtained with both PPG PO and PPG VC were associated with changes in heart rate ( p < 0.001), stroke volume ( p < 0.001), and pulse pressure ( p < 0.001). Furthermore, they provided an earlier detection of hemodynamic shock relative to the traditional metrics of shock index ( p < 0.001 for both), systolic blood pressure ( p < 0.001 for both), and heart rate ( p = 0.001 for both). The CRM obtained from PPG PO provides a valid, time-sensitized prediction of hemodynamic decompensation, opening the door to provide military medical personnel noninvasive in-field advanced capability for early detection of hemorrhage and imminent onset of shock. Diagnostic Tests or Criteria; Level III.

Unveiling ecological/evolutionary insights in HIV viral load dynamics: Allowing random slopes to observe correlational changes to CpG-contents and other molecular and clinical predictors

In the context of infectious diseases, the dynamic interplay between ever-changing host populations and viral biology demands a more flexible modeling approach than common fixed correlations. Embracing random-effects regression models allows for a nuanced understanding of the intricate ecological and evolutionary dynamics underlying complex phenomena, offering valuable insights into disease progression and transmission patterns. In this article, we employed a random-effects regression to model an observed decreasing median plasma viral load (pVL) among individuals with HIV in Mexico City during 2019–2021. We identified how these functional slope changes (i.e. random slopes by year) improved predictions of the observed pVL median changes between 2019 and 2021, leading us to hypothesize underlying ecological and evolutionary factors. Our analysis involved a dataset of pVL values from 7325 ART-naïve individuals living with HIV, accompanied by their associated clinical and viral molecular predictors. A conventional fixed-effects linear model revealed significant correlations between pVL and predictors that evolved over time. However, this fixed-effects model could not fully explain the reduction in median pVL; thus, prompting us to adopt random-effects models. After applying a random effects regression model—with random slopes and intercepts by year—, we observed potential "functional changes" within the local HIV viral population, highlighting the importance of ecological and evolutionary considerations in HIV dynamics: A notably stronger negative correlation emerged between HIV pVL and the CpG content in the pol gene, suggesting a changing immune landscape influenced by CpG-induced innate immune responses that could impact viral load dynamics. Our study underscores the significance of random effects models in capturing dynamic correlations and the crucial role of molecular characteristics like CpG content. By enriching our understanding of changing host-virus interactions and HIV progression, our findings contribute to the broader relevance of such models in infectious disease research. They shed light on the changing interplay between host and pathogen, driving us closer to more effective strategies for managing infectious diseases. Significance of the studyThis study highlights a decreasing trend in median plasma viral loads among ART-naïve individuals living with HIV in Mexico City between 2019 and 2021. It uncovers various predictors significantly correlated with pVL, shedding light on the complex interplay between host-virus interactions and disease progression. By employing a random-slopes model, the researchers move beyond traditional fixed-effects models to better capture dynamic correlations and evolutionary changes in HIV dynamics. The discovery of a stronger negative correlation between pVL and CpG content in HIV-pol sequences suggests potential changes in the immune landscape and innate immune responses, opening avenues for further research into adaptive changes and responses to environmental shifts in the context of HIV infection. The study's emphasis on molecular characteristics as predictors of pVL adds valuable insights to epidemiological and evolutionary studies of viruses, providing new avenues for understanding and managing HIV infection at the population level.

Physiologic Validation of the Compensatory Reserve Metric Obtained From Pulse Oximetry Waveforms

Background: The compensatory reserve metric (CRM) provides a novel marker of hemodynamic status in prediction of sudden cardiovascular decompensation during central hypovolemia. The CRM has previously been calculated using arterial waveforms obtained from a photoplethysmographic volume-clamp technique. However, the in-field use of pulse oximetry is becoming more prominent in research and medicine. To improve in-field applicability of the CRM, this project aimed to validate pulse-oximetry derived CRM values relative to physiologic data during simulated hemorrhage through application of lower body negative pressure (LBNP). Methods: Forty-nine healthy adults (25 females) underwent a graded LBNP protocol with the following 5-minute stages: -0, -15, -30, -45, -60, -70, -80, -90, and 100 mmHg, or until the onset of pre-syncopal symptoms (tolerance) was reached. Arterial waveforms were sampled using pulse oximetry (Massimo Radical 7). The CRM was calculated using a validated one-dimensional convolutional neural network. A brachial artery catheter was used to measure intraarterial pressure. A 3-lead ECG was used to measure heart rate. SpO2 was measured using pulse oximetry. Cardiac output and stroke volume were estimated using the photoplethysmographic volume-clamp. Data were binned for the last thirty seconds of each completed stage, and at tolerance. Fixed-effect linear mixed models with repeated measures were used to examine the association between CRM values and physiologic variables. A priori significance was set at P&lt;0.05. Results: The median LBNP stage reached was 70 mmHg (Range: 45-100 mmHg). Relative to baseline, at tolerance there was a 50±12% ( P&lt;0.001) mean reduction in stroke volume, 65±27% ( P&lt;0.001) increase in heart rate, 18±8% ( P&lt;0.001) reduction in mean arterial pressure, 21±7% ( P&lt;0.001) systolic blood pressure, 8±9% ( P&lt;0.001) diastolic blood pressure, and 39±12% ( P&lt;0.001) pulse pressure. The CRM obtained using pulse oximetry was significantly associated with a reduction in stroke volume ( P&lt;0.001), increase in heart rate ( P&lt;0.001), and reductions in systolic ( P=0.033), diastolic ( P=0.036), and pulse pressure ( P=0.002). There was no statistically significant association between CRM and cardiac output ( P=0.421), SpO2 ( P=0.408), or mean arterial pressure ( P=0.214). Conclusion: The CRM obtained using pulse oximetry may be a valid, reliable marker of hemodynamic status with promising in-field applications. Future studies warrant investigation of feasibility and applicability within various contexts ranging from the operating room to the battlefield. The presented work was funded in part by the Congressionally Directed Medical Research Program (Award No. DM180240) and Offce of Naval Research (Awards No. N00014-18-D-7001 and N00014-19-C-2017). This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Changes in Chlamydia trachomatis risk before and after union formation and separation among women of reproductive age.

Not having an established relationship is associated with an elevated risk of Chlamydia trachomatis (CT) infection, but this might reflect selection into and out of unions. Although union formation and union separation are common events in reproductive age, little is known about changes in CT risk before and after these transitions. We linked Finnish Population Register data to the National Register of Infectious Diseases and used fixed-effects linear probability models that account for all time-invariant confounders to examine changes in women's 6-month CT risk 3 years before and 3 years after entry into first cohabitation (n = 293554), non-marital separation (n = 201647) or marital separation (n = 92232) during 2005-14. From 3 years to 1 year before first union formation, the 6-month risk of CT increased slightly, peaking at 1.27% immediately prior to union formation (95% confidence interval 1.22-1.31). It declined sharply following union formation, being only 0.40% (0.34-0.46) 6-12 months after union formation with little changes thereafter. Among women separating from non-marital unions, the risk increased from 0.50% (0.42-0.57) to 1.45% (1.40-1.49) around the time of separation and decreased following separation. The pattern of findings was relatively similar for marital separation, although the observed risks and changes were smaller in magnitude. Our results based on longitudinal data and individual fixed-effects models indicate that the period immediately after separation may be causally associated with an elevated risk of CT. This suggests that recently separated women should be identified as a high-risk group for CT.

Examining the maintenance of dialect features in colloquial urban Armenian speech via variationist analysis of vowels in Gavaṛ, Armenia

This study examines the maintenance of previously described local dialect vowels in the regional city of Gavaṛ, Armenia. The dialect vowel system contains additional phonemic and allophonic distinctions not found in supralocal Armenian varieties. As such, adherence to this system was conceptualized through the presence or absence of various vowel mergers. F1 and F2 were measured from picture and word list data collected from sociolinguistic interviews with 31 participants. Mergers were assessed for each participant via Pillai scores and Euclidean distances between clusters of words where different vowels were predicted to appear based on previous descriptions of the dialect. Countering previous claims about dialect leveling in regional cities, some participants were found to maintain some aspects of the dialect vowel system. Fixed effects linear models assessed the effect of demographic predictors (self-reported gender, birth year, education level) on maintenance of dialect vowels. There was an effect of gender, such that men were found to maintain some dialect vowels to a greater degree than women. Participants’ commentary suggested that the most salient aspects of the dialect vowel system are the same ones in relation to which this demographic variation was uncovered, indicating a relationship between salience and maintenance of dialect vowels.

Simplified Methods for Modelling Dependent Parameters in Health Economic Evaluations: A Tutorial.

In health economic evaluations, model parameters are often dependent on other model parameters. Although methods exist to simulate multivariate normal (MVN) distribution data and estimate transition probabilities in Markov models while considering competing risks, they are technically challenging for health economic modellers to implement. This tutorial introduces easily implementable applications for handling dependent parameters in modelling. Analytical proofs and proposed simplified methods for handling dependent parameters in typical health economic modelling scenarios are provided, and implementation of these methods are illustrated in seven examples along with the SAS and R code. Methods to quantify the covariance and correlation coefficients of correlated variables based on published summary statistics and generation of MVN distribution data are demonstrated using examples of physician visits data and cost component data. The use of univariate normal distribution data instead of MVN distribution data to capture population heterogeneity is illustrated based on the results from multiple regression models with linear predictors, and two examples are provided (linear fixed-effects model and Cox proportional hazards model). A conditional probability method is introduced to handle two or more state transitions in a single Markov model cycle and applied in examples of one- and two-way state transitions. This tutorial proposes an extension of routinely used methods along with several examples. These simplified methods may be easily applied by health economic modellers with varied statistical backgrounds.

Ambient air pollution and consumer spending: Evidence from Spain.

Research on the economic burden of air pollution has focused primarily on its macroeconomic impact. However, as some studies have found that air pollution can lead to avoidance behavior-for example, reducing the time spent outdoors-we hypothesize that it can also influence consumer spending activity. We combine high frequency data on ozone and fine particulate pollution with daily consumer spending in brick-and-mortar retail in 129 postal codes in Spain during 2014 to estimate the association between the two. Using a linear fixed effects model, we find that a 1-standard deviation increase in ozone concentration (20.97 μg/m3) is associated with 3.9 percent decrease in consumer spending (95% CI: -0.066, -0.012; p<0.01). The association of fine particulate matter with consumer spending is, however, not statistically significant (β: 0.005; 95% CI: -0.009, 0.018; p>0.10). Further, we do not observe a sufficiently strong bounce-back in consumer spending in the day-or even the week-following higher ozone concentration. Also, we find that the relationship between ozone concentration and consumer spending is heterogeneous, with those aged below 25 and those aged 45 or above exhibiting stronger negative association. This research informs policymakers about a plausibly unaccounted cost of ambient air pollution, even at concentrations lower than the WHO air quality guideline for short-term exposure.

Physical illness and changes in spousal depression: a register study on Finnish middle-aged couples

Abstract Background Physical health decline may affect family members’ mental health by causing distress and, in case of functional impairments, need to provide care. We examined how diseases common in midlife but with different disease progression and level of impairment are associated with short-term and long-term changes in spousal depression. Methods We used Finnish total population register data from 2000-2019 to identify 91,849 men and 70,836 women aged 30-70 that experienced onset of severe diseases without cognitive impairment (myocardial infarction, prostate cancer, breast cancer), conditions with sudden onset and immediate impairment (stroke, traumatic brain injury) or progressive conditions with increasing impairment (Parkinson's disease, multiple sclerosis, dementia) while living with a spouse. We measured depression with antidepressant purchases and used fixed-effects linear probability models to examine spouses’ depression trajectories before and after onset of spousal disease Results Preliminary findings show that the onset of any type of spousal illness is associated with an increase in depression. Among men this increase is similar in magnitude irrespective of the type of spouse's illness, whereas among women the increase is smaller if the spouse is diagnosed with a disease without cognitive impairment. When the spouse is diagnosed with a progressive condition, female spouses’ depression increases more gradually, whereas a large immediate increase in depression follows sudden onset conditions. One year after diagnosis there are little changes in spousal depression. Conclusions Diseases common in midlife increase spouse's risk of depression around the time of diagnosis, and the effect appears persistent. Adequate support should thus be available to family members from the start of physical illness. When planning support to female spouses, the male spouse's cognitive impairment and associated care needs should be carefully evaluated. Key messages • Diseases common in midlife increase spouse's depression risk around the time of diagnosis, and the effect appears persistent. Support to spouses should be available from the start of illness. • Cognitive impairment of the male spouse seems to increase female spouse's depression particularly strongly, suggesting that caregiving help could be especially beneficial for women.

Free compulsory education can mitigate COVID-19 disruptions’ adverse effects on child schooling

Developing countries are increasingly under siege from various adverse income shocks, including climate hazards and public health crises, which are known to increase households’ opportunity cost of child schooling. This paper uses an individual fixed-effect linear probability model to test whether free compulsory education mitigates the permanent effect of COVID-19’s containment measures on children’s school attendance. In so doing, we exploit the variation across levels of education in the implementation of free compulsory education laws in Nigeria. Estimation results show that fifteen months after schools reopened, COVID-19’s containment measures had no permanent effect on the school attendance of children whose schooling was free and compulsory. However, they decreased the school attendance of those whose schooling was neither free nor compulsory by 7.8 percentage points. Our findings suggest that pre-existing education policies, such as the scale of implementation of compulsory education laws, influence children’s vulnerability to the negative effects of adverse aggregate income shocks on children’s schooling outcomes.

Characterizing temporal trends in populations exposed to aircraft noise around U.S. airports: 1995-2015.

Aircraft noise is a key concern for communities surrounding airports, with increasing evidence for health effects and inequitable distributions of exposure. However, there have been limited national-scale assessments of aircraft noise exposure over time and across noise metrics, limiting evaluation of population exposure patterns. We evaluated national-scale temporal trends in aviation noise exposure by airport characteristics and across racial/ethnic populations in the U.S. Noise contours were modeled for 90 U.S. airports in 5-year intervals between 1995 and 2015 using the Federal Aviation Administration's Aviation Environmental Design Tool. We utilized linear fixed effects models to estimate changes in noise exposure areas for day-night average sound levels (DNL) of 45, 65, and a nighttime equivalent sound level (Lnight) of 45 A-weighted decibels (dB[A]). We used group-based trajectory modeling to identify distinct groups of airports sharing underlying characteristics. We overlaid noise contours and Census tract data from the U.S. Census Bureau and American Community Surveys for 2000 to 2015 to estimate exposure changes overall and by race/ethnicity. National-scale analyses showed non-monotonic trends in mean exposed areas that peaked in 2000, followed by a 37% decrease from 2005 to 2010 and a subsequent increase in 2015. We identified four distinct trajectory groups of airports sharing latent characteristics related to size and activity patterns. Those populations identifying as minority (e.g., Hispanic/Latino, Black/African American, Asian) experienced higher proportions of exposure relative to their subgroup populations compared to non-Hispanic or White populations across all years, indicating ethnic and racial disparities in airport noise exposure that persist over time. Overall, these data identified differential exposure trends across airports and subpopulations, helping to identify vulnerable communities for aviation noise in the U.S. We conducted a descriptive analysis of temporal trends in aviation noise exposure in the U.S. at a national level. Using data from 90 U.S. airports over a span of two decades, we characterized the noise exposure trends overall and by airport characteristics, while estimating the numbers of exposed by population demographics to help identify the impact on vulnerable communities who may bear the burden of aircraft noise exposure.

Long-term economic impacts of no-till adoption

No-till has long been considered a sustainable agricultural practice because of its potential to provide on-farm productivity benefits as well as off-site environmental benefits. However, “economic concerns” have been identified as one of the largest barriers to adopting no-till (i.e., costs associated with adoption possibly being greater than the returns in the short term). This study evaluates the long-term economic impact of no-till adoption using rich plot-level data from a long-term field experiment over the period 1996–2019. Linear fixed-effect models and partial budgeting techniques are used in the empirical analysis. Estimation results reveal that there are generally no statistically significant differences between long-term yields from no-till relative to the conventional tillage practice when considering corn, soybean, and wheat. Nonetheless, the partial budgeting analysis using the long-term data suggests that net returns (or profits) per acre tend to be greater for no-till compared to conventional tillage for all three crops. This is primarily due to the statistically lower farm operation costs associated with no-till. Moreover, our analysis also suggests that relative profitability of no-till increases as the practice is used longer over time. This insight supports suggestions from previous studies that long-term adoption of continuous no-till is important to best realize the benefits from the practice.

Does renewable energy help increase life expectancy? Insight from the linking renewable energy, economic growth, and life expectancy in 121 countries

Although there are many studies on the social welfare of renewable energy, the systematic study of the impact of renewable energy on life expectancy is relatively rare. Aiming at filling the research gap, we incorporate renewable energy consumption, economic growth, and life expectancy into a framework to study the relationship between them using the linear fixed-effect model and non-linear panel threshold model. Both the fixed-effect model and the threshold model results show a positive relationship between renewable energy consumption and life expectancy. Renewable energy consumption has a double threshold effect of per capita GDP on life expectancy. As per capita GDP crosses these two thresholds in turn, the correlation coefficient between renewable energy consumption and life expectancy increases. In addition, the relationship between renewable energy and life expectancy varies across income groups. The correlation between renewable energy consumption and life expectancy in the high-income group is the highest among all income groups, implying that renewable energy consumption is more helpful in increasing life expectancy in high-income countries. We call for the integration of health policy and renewable energy policy so that renewable energy generates greater health benefits.

Linear panel regressions with two-way unobserved heterogeneity

We study linear panel regression models in which the unobserved error term is an unknown smooth function of two-way unobserved fixed effects. In standard additive or interactive fixed effect models the individual specific and time specific effects are assumed to enter with a known functional form (additive or multiplicative). In this paper, we allow for this functional form to be more general and unknown. We discuss two different estimation approaches that allow consistent estimation of the regression parameters in this setting as the number of individuals and the number of time periods grow to infinity. The first approach uses the interactive fixed effect estimator in Bai (2009), which is still applicable here, as long as the number of factors in the estimation grows asymptotically. The second approach first discretizes the two-way unobserved heterogeneity (similar to what Bonhomme et al., 2021 are doing for one-way heterogeneity) and then estimates a simple linear fixed effect model with additive two-way grouped fixed effects. For both estimation methods we obtain asymptotic convergence results, perform Monte Carlo simulations, and employ the estimators in an empirical application to UK house price data.

Scarce Evidence of Heterosis for Growth Traits in Peruvian Guinea Pigs.

This study aimed to estimate the heterosis for productive traits in a two-way crossbreeding scheme. Four guinea pig lines were originally selected for the following traits: line P1 for the growth rate, P2 for the partial feed conversion rate, M1 for the growth rate of the litter at 10 days of age, and M2 for the litter size at birth. The comparison included 176 purebreds (P1: 46, P2: 43, M1: 54 and M2: 33) and 150 crosses (P1P2: 42, P2P1: 38, M1M2: 11 and M2M1: 59); body weights at birth, 10 days, weaning and 60 days of age were analyzed. A linear fixed-effect model was used, and heterosis was estimated as the difference between the average performance of the crossbred and pure-line animals. The pure line comparisons showed that P2 was lower than P1 for weight at 10 days and weaning weight, while all other comparisons between the paternal and maternal pure lines were not significant. The results indicated significant positive heterosis effects for both types of crosses, but only for birth weight: 3.7% for paternal crosses and 12.7% for maternal crosses. The heterosis estimates were mostly positive but not significant for all other traits. A reason for the low levels of heterosis could be that the lines are not very genetically differentiated. These results suggest that applying a two-way crossbreeding scheme within paternal and maternal guinea pig lines for meat production is not recommended due to the absence of heterosis for growth traits.

Academic freedom and the onset of autocratization

ABSTRACT Democracy is under threat across the globe and a third wave of autocratization manifests in democratic regression and authoritarian hardening. However, although universities have been important pro-democracy hotbeds, the nexus between academic freedom and autocratization has generated little scholarly attention. This article presents the first systematic investigation of the influence of academic freedom on the onset of autocratization. In particular, it reveals how academic freedom protects regimes from an onset of autocratization and argues that more academic freedom reduces the risk of autocratization by imprinting a pro-democracy bias on students and researchers. This article’s research design combines two studies. Study I tests whether graduates that were socialized under more academic freedom develop more democratic support, which I analyse using data from the World Values Surveys and linear fixed effects models. Study II tests whether more academic freedom reduces the onset probability of autocratization using V-Dem data and binomial-response GLMs. This article finds evidence that while high levels of academic freedom reduce the probability of an onset of autocratization, low levels also reduce the probability of an onset. Overall, the article highlights the crucial role of academic freedom for democracy, especially in times of severe threats to democracy.

Potential impacts of seasonal and altitudinal changes on enzymatic peat decomposition in the High Andean Paramo region of Ecuador

The Andean Paramo is a vast ecosystem, characterized by distinct vegetational zones at several altitudinal levels with huge water storage and carbon fixation capacity within its peat-like andosols, due to a slow decomposition rate of organic matter. These characteristics become mutually related as enzymatic activities increase with temperature and are associated with oxygen penetration, restricting the activity of many hydrolytic enzymes according to the enzyme Latch Theory. This study describes the changing activity of sulfatase (Sulf), phosphatase (Phos), n-acetyl-glucosaminidase (N-Ac), cellobiohydrolase (Cellobio), β-glucosidase (β-Glu), and peroxidase (POX) on an altitudinal scale from 3600 to 4200 m, in rainy and dry seasons at 10 and 30 cm sampling depth, related to physical and chemical soil characteristics, like metals and organic elements. Linear fixed-effect models were established to analyze these environmental factors to determine distinct decomposition patterns. The data suggests a strong tendency towards decreasing enzyme activities at higher altitudes and in the dry season up to two-fold stronger activation for Sulf, Phos, Cellobio, and β-Glu. Especially the lowest altitude showed considerably stronger activity of N-Ac, β-Glu, and POX. Although sampling depth revealed significant differences for all hydrolases but Cellobio, it had minor effects on model outcomes. Further organic rather than physical or metal components of the soil explain the enzyme activity variations. Although the levels of phenols coincided mostly with the soil organic carbon content, there was no direct relation between hydrolases, POX activity, and phenolic substances. The outcome suggests that slight environmental changes with global warming might cause important changes in enzyme activities leading to increased organic matter decomposition at the borderline between the paramo region and downslope ecosystems. Expected extremer dry seasons could cause critical changes as aeration increases peat decomposition leading to a constant liberation of carbon stocks, which puts the paramo region and its ecosystem services in great danger.

UK long-term monitoring dataset: assessing factors affecting biomarkers commonly used in environmental programmes

Long-term programmes like the UK Clean Seas Environmental Monitoring Programme (CSEMP) rely on biological effects techniques, including biomarkers, to assess if chemical pollutants are affecting sentinel species in the aquatic environment. In this study, we have applied mixed and fixed effect linear models to the long-term CSEMP dataset (2005-2018) to evaluate if factors such as region (location), sex, age, gonadosomatic index (GSI) and condition factor (CF), contribute to the variability observed in the levels of 3 well established biomarkers (inhibition of acetylcholinesterase in muscle-AChE, induction of hepatic 7-ethoxyresorufin-O-deethylase-EROD and presence of biliary 1-hydroxypyrene-1-OH pyrene) used to monitor biological effects of contaminants in dab (Limanda limanda) around UK waters. Regional differences (location) were a significant explanatory variable for the 3 biomarkers. Substantial differences were found in regional average muscle AChE activity, overall indicating the East Coast regions as likely more impacted by acetylcholinesterase inhibitors (e.g. organophosphates and carbamates). We report for the first time that, while accounting for region, sex and gonadosomatic index are significant predictors of muscle acetylcholinesterase isoform in dab (R2 = 0.13-0.15), and therefore advise the future analysis of this marker should be done by sex when reporting for marine environmental purposes. Dab condition factor is also a significant predictor for both enzymatic markers (AChE and EROD) but not for 1-OH pyrene. Sex and age, and their interaction, were the strongest variables (R2 = 0.46) influencing hepatic EROD, showing that although overall females had higher hepatic EROD, male dab hepatic EROD increased with age. Correlations between the three biomarkers might assist in discerning types of prevalent regional contamination over the studied period. Our results highlight the factors to account for when assessing if environmental contamination is contributing to the responses of these 3 biomarkers in dab, and other flatfish species, used in marine environmental monitoring programmes.

Changes in anxiety and depression symptoms during the Covid-19 lockdown in the Netherlands. The moderating role of pre-existing mental health, employment situation and alcohol consumption.

Evidence suggests an increase of depression and anxiety symptoms during the Covid-19 pandemic but most studies relied on cross-sectional designs and/or small samples, and they often overlooked subgroup effects in the impact of the lockdown. We investigated the effect of the pandemic on depression and anxiety symptoms, and whether it differed by employment situation and alcohol consumption. This longitudinal study used 23 waves of the Covid-Questionnaire (April 2020-July 2021), within the Lifelines cohort from the Netherlands (n = 76,254). Depression and anxiety symptoms were combined in a "mental health score". Linear fixed-effects models were fitted to analyse trends in mental health throughout the observation period. The moderating role of pre-existing mental health, employment situation, and alcohol consumption was tested. Depression and anxiety symptoms fluctuated considerably during the observation period, with clear peaks in winter 2021, during the strictest lockdown period. Moreover, temporal patterns differed by employment situation and alcohol consumption patterns, suggesting that various subgroups reacted to the pandemic and the lockdown in different ways. Lockdowns increased depression and anxiety symptoms in the Netherlands. The effect was particularly strong for unemployed individuals, those with risky alcohol consumption patterns and those with pre-existing mental health disorders.