A biologist's guide to model selection and causal inference

Human immune and metabolic biomarker levels, and stress-biomarker associations, differ by season: Implications for biomedical health research

Although seasonal changes in physiology are well documented, little is known about how human immune and metabolic markers vary across seasons, and no studies have examined how stress → health biomarker associations differ across the year. To investigate these issues, we analyzed data from 2118 participants of the Midlife in the United States (MIDUS) study to determine whether there were differences in (a) levels of 19 immune and metabolic markers, and (b) the association between perceived stress and each biomarker across the year. Results of component-wide boosted generalized additive models revealed seasonal patterning for most biomarkers, with immune proteins generally peaking when days were shorter. Moreover, whereas levels of hemoglobin A1C rose from late fall to spring, triglycerides were elevated in the summer and fall, and high-density lipoprotein decreased steadily from January to December. Urinary cortisol and cortisone exhibited opposite patterns, peaking at the beginning and end of the year, respectively. Most critically, we found that the effects of perceived stress on 18 of the 19 health biomarkers assessed varied by month of measurement. In some cases, these differences involved the magnitude of the stress → biomarker association but, in other cases, it was the direction of the effect that changed. Studies that do not account for month of biomarker assessment may thus yield misleading or unreproducible results.

Little evidence of inbreeding depression for birth mass, survival and growth in Antarctic fur seal pups

Inbreeding depression, the loss of offspring fitness due to consanguineous mating, is generally detrimental for individual performance and population viability. We investigated inbreeding effects in a declining population of Antarctic fur seals (Arctocephalus gazella) at Bird Island, South Georgia. Here, localised warming has reduced the availability of the seal's staple diet, Antarctic krill, leading to a temporal increase in the strength of selection against inbred offspring, which are increasingly failing to recruit into the adult breeding population. However, it remains unclear whether selection operates before or after nutritional independence at weaning. We therefore used microsatellite data from 885 pups and their mothers, and SNP array data from 98 mother-offspring pairs, to quantify the effects of individual and maternal inbreeding on three important neonatal fitness traits: birth mass, survival and growth. We did not find any clear or consistent effects of offspring or maternal inbreeding on any of these traits. This suggests that selection filters inbred individuals out of the population as juveniles during the time window between weaning and recruitment. Our study brings into focus a poorly understood life-history stage and emphasises the importance of understanding the ecology and threats facing juvenile pinnipeds.

Evaluating the influence of marine protected areas on surf zone fish

Marine protected areas (MPAs) globally serve conservation and fisheries management goals, generating positive effects in some marine ecosystems. Surf zones and sandy beaches, critical ecotones bridging land and sea, play a pivotal role in the life cycles of numerous fish species and serve as prime areas for subsistence and recreational fishing. Despite their significance, these areas remain understudied when evaluating the effects of MPAs. We compared surf zone fish assemblages inside and outside MPAs across 3 bioregions in California (USA). Using seines and baited remote underwater videos (BRUVs), we found differences in surf zone fish inside and outside MPAs in one region. Inside south region MPAs, we observed higher abundance (Tukey's honest significant difference [HSD] = 0.83, p = 0.0001) and richness (HSD = 0.22, p = 0.0001) in BRUVs and greater biomass (HSD = 0.32, p = 0.0002) in seine surveys compared with reference sites. Selected live-bearing, fished taxa were positively affected by MPAs. Elasmobranchs displayed greater abundance in BRUV surveys and higher biomass in seine surveys inside south region MPAs (HSD = 0.35, p = 0.0003 and HSD = 0.23, p = 0.008, respectively). Although we observed no overall MPA signal for Embiotocidae, abundances of juvenile and large adult barred surfperch (Amphistichus argenteus), the most abundant fished species, were higher inside MPAs (K-S test D = 0.19, p < 0.0001). Influence of habitat characteristics on MPA performance indicated surf zone width was positively associated with fish abundance and biomass but negatively associated with richness. The south region had the largest positive effect size on all MPA performance metrics. Our findings underscored the variability in species richness and composition across regions and survey methods that significantly affected differences observed inside and outside MPAs. A comprehensive assessment of MPA performance should consider specific taxa, their distribution, and the effects of habitat factors and geography.

When indices disagree: facing conceptual and practical challenges

Hypothesis testing requires meaningful ways to quantify biological phenomena and account for alternative mechanisms that could explain the same pattern. Researchers combine experiments, statistics, and indices to account for these confounding mechanisms. Key concepts in ecology and evolution, such as niche breadth (NB) or fitness, can be represented by several indices, which often provide uncorrelated estimates. Is this because the indices use different types of noisy data or because the targeted phenomenon is complex and multidimensional? We discuss implications of these scenarios and propose five steps to aid researchers in identifying and combining indices, experiments, and statistics. Building on prior efforts to construct databases of hypotheses and indices and document assumptions, these steps help provide a formal strategy to reduce self-confirmatory bias.

Glucagon-Like Peptide-1 Receptor Agonist Use and Residual Gastric Content Before Anesthesia

Importance

Glucagon-like peptide-1 receptor agonist (GLP-1 RA) use is rapidly increasing in the US, driven by its expanded approval for weight management in addition to hyperglycemia management in patients with type 2 diabetes. The perioperative safety of these medications, particularly with aspiration risk under anesthesia, is uncertain.

Objective

To assess the association between GLP-1 RA use and prevalence of increased residual gastric content (RGC), a major risk factor for aspiration under anesthesia, using gastric ultrasonography.

Design, Setting, and Participants

This cross-sectional study prospectively enrolled patients from a large, tertiary, university-affiliated hospital from June 6 through July 12, 2023. Participants followed preprocedural fasting guidelines before an elective procedure under anesthesia. Patients with altered gastric anatomy (eg, from previous gastric surgery), pregnancy, recent trauma (<1 month), or an inability to lie in the right lateral decubitus position for gastric ultrasonography were excluded.

Exposure

Use of a once-weekly GLP-1 RA.

Main Outcomes and Measures

The primary outcome was the presence of increased RGC, defined by the presence of solids, thick liquids, or more than 1.5 mL/kg of clear liquids on gastric ultrasonography. Analysis was adjusted for confounders using augmented inverse probability of treatment weighting, a propensity score-based technique. Secondarily, the association between the duration of drug interruption and the prevalence of increased RGC was explored.

Results

Among the 124 participants (median age, 56 years [IQR, 46-65 years]; 75 [60%] female), the prevalence of increased RGC was 56% (35 of 62) in patients with GLP-1 RA use (exposure group) compared with 19% (12 of 62) in patients who were not taking a GLP-1 RA drug (control group). After adjustment for confounding, GLP-1 RA use was associated with a 30.5% (95% CI, 9.9%-51.2%) higher prevalence of increased RGC (adjusted prevalence ratio, 2.48; 95% CI, 1.23-4.97). There was no association between the duration of GLP-1 RA interruption and the prevalence of increased RGC (adjusted odds ratio, 0.86; 95% CI, 0.65-1.14).

Conclusions and Relevance

Use of a GLP-1 RA was independently associated with increased RGC on preprocedural gastric ultrasonography. The findings suggest that the preprocedural fasting duration suggested by current guidelines may be inadequate in this group of patients at increased risk of aspiration under anesthesia.

Latitudinal patterns in stabilizing density dependence of forest communities

Numerous studies have shown reduced performance in plants that are surrounded by neighbours of the same species1,2, a phenomenon known as conspecific negative density dependence (CNDD)3. A long-held ecological hypothesis posits that CNDD is more pronounced in tropical than in temperate forests4,5, which increases community stabilization, species coexistence and the diversity of local tree species6,7. Previous analyses supporting such a latitudinal gradient in CNDD8,9 have suffered from methodological limitations related to the use of static data10-12. Here we present a comprehensive assessment of latitudinal CNDD patterns using dynamic mortality data to estimate species-site-specific CNDD across 23 sites. Averaged across species, we found that stabilizing CNDD was present at all except one site, but that average stabilizing CNDD was not stronger toward the tropics. However, in tropical tree communities, rare and intermediate abundant species experienced stronger stabilizing CNDD than did common species. This pattern was absent in temperate forests, which suggests that CNDD influences species abundances more strongly in tropical forests than it does in temperate ones13. We also found that interspecific variation in CNDD, which might attenuate its stabilizing effect on species diversity14,15, was high but not significantly different across latitudes. Although the consequences of these patterns for latitudinal diversity gradients are difficult to evaluate, we speculate that a more effective regulation of population abundances could translate into greater stabilization of tropical tree communities and thus contribute to the high local diversity of tropical forests.

Precision stratification of prognostic risk factors associated with outcomes in gestational diabetes mellitus: a systematic review

BACKGROUND

The objective of this systematic review is to identify prognostic factors among women and their offspring affected by gestational diabetes mellitus (GDM), focusing on endpoints of cardiovascular disease (CVD) and type 2 diabetes (T2D) for women, and cardiometabolic profile for offspring.

METHODS

This review included studies published in English language from January 1st, 1990, through September 30th, 2021, that focused on the above outcomes of interest with respect to sociodemographic factors, lifestyle and behavioral characteristics, traditional clinical traits, and 'omics biomarkers in the mothers and offspring during the perinatal/postpartum periods and across the lifecourse. Studies that did not report associations of prognostic factors with outcomes of interest among GDM-exposed women or children were excluded.

RESULTS

Here, we identified 109 publications comprising 98 observational studies and 11 randomized-controlled trials. Findings indicate that GDM severity, maternal obesity, race/ethnicity, and unhealthy diet and physical activity levels predict T2D and CVD in women, and greater cardiometabolic risk in offspring. However, using the Diabetes Canada 2018 Clinical Practice Guidelines for studies, the level of evidence was low due to potential for confounding, reverse causation, and selection biases.

CONCLUSIONS

GDM pregnancies with greater severity, as well as those accompanied by maternal obesity, unhealthy diet, and low physical activity, as well as cases that occur among women who identify as racial/ethnic minorities are associated with worse cardiometabolic prognosis in mothers and offspring. However, given the low quality of evidence, prospective studies with detailed covariate data collection and high fidelity of follow-up are warranted.

Drivers of arthropod biodiversity in an urban ecosystem

Our world is becoming increasingly urbanized with a growing human population concentrated around cities. The expansion of urban areas has important consequences for biodiversity, yet the abiotic drivers of biodiversity in urban ecosystems have not been well characterized for the most diverse group of animals on the planet, arthropods. Given their great diversity, comparatively small home ranges, and ability to disperse, arthropods make an excellent model for studying which factors can most accurately predict urban biodiversity. We assessed the effects of (i) topography (distance to natural areas and to ocean) (ii) abiotic factors (mean annual temperature and diurnal range), and (iii) anthropogenic drivers (land value and amount of impervious surface) on the occurrence of six arthropod groups represented in Malaise trap collections run by the BioSCAN project across the Greater Los Angeles Area. We found striking heterogeneity in responses to all factors both within and between taxonomic groups. Diurnal temperature range had a consistently negative effect on occupancy but this effect was only significant in Phoridae. Anthropogenic drivers had mixed though mostly insignificant effects, as some groups and species were most diverse in highly urbanized areas, while other groups showed suppressed diversity. Only Phoridae was significantly affected by land value, where most species were more likely to occur in areas with lower land value. Los Angeles can support high regional arthropod diversity, but spatial community composition is highly dependent on the taxonomic group.

Uniting Experiments and Big Data to advance ecology and conservation

Many ecologists increasingly advocate for research frameworks centered on the use of 'big data' to address anthropogenic impacts on ecosystems. Yet, experiments are often considered essential for identifying mechanisms and informing conservation interventions. We highlight the complementarity of these research frameworks and expose largely untapped opportunities for combining them to speed advancements in ecology and conservation. With nascent but increasing application of model integration, we argue that there is an urgent need to unite experimental and big data frameworks throughout the scientific process. Such an integrated framework offers potential for capitalizing on the benefits of both frameworks to gain rapid and reliable answers to ecological challenges.

Neighbours and relatives: accounting for spatial distribution when testing causal hypotheses in cultural evolution

Many important and interesting hypotheses about cultural evolution are evaluated using cross-cultural correlations: if knowing one particular feature of a culture (e.g. environmental conditions such as temperature, humidity or parasite load) allows you to predict other features (e.g. language features, religious beliefs, cuisine), it is often interpreted as indicating a causal link between the two (e.g. hotter climates carry greater disease risk, which encourages belief in supernatural forces and favours the use of antimicrobial ingredients in food preparation; dry climates make the production of distinct tones more difficult). However, testing such hypotheses from cross-cultural comparisons requires us to take proximity of cultures into account: nearby cultures share many aspects of their environment and are more likely to be similar in many culturally inherited traits. This can generate indirect associations between environment and culture which could be misinterpreted as signals of a direct causal link. Evaluating examples of cross-cultural correlations from the literature, we show that significant correlations interpreted as causal relationships can often be explained as a result of similarity between neighbouring cultures. We discuss some strategies for sorting the explanatory wheat from the co-varying chaff, distinguishing incidental correlations from causal relationships.

Novel Metabolic Subtypes in Pregnant Women and Risk of Early Childhood Obesity in Offspring

Importance

The in utero metabolic milieu is associated with offspring adiposity. Standard definitions of maternal obesity (according to prepregnancy body mass index [BMI]) and gestational diabetes (GDM) may not be adequate to capture subtle yet important differences in the intrauterine environment that could be involved in programming.

Objectives

To identify maternal metabolic subgroups during pregnancy and to examine associations of subgroup classification with adiposity traits in their children.

Design, Setting, and Participants

This cohort study included mother-offspring pairs in the Healthy Start prebirth cohort (enrollment: 2010-2014) recruited from University of Colorado Hospital obstetrics clinics in Aurora, Colorado. Follow-up of women and children is ongoing. Data were analyzed from March to December 2022.

Exposures

Metabolic subtypes of pregnant women ascertained by applying k-means clustering on 7 biomarkers and 2 biomarker indices measured at approximately 17 gestational weeks: glucose, insulin, Homeostatic Model Assessment for Insulin Resistance, total cholesterol, high-density lipoprotein cholesterol (HDL-C), triglycerides, free fatty acids (FFA), HDL-C:triglycerides ratio, and tumor necrosis factor α.

Main Outcomes and Measures

Offspring birthweight z score and neonatal fat mass percentage (FM%). In childhood at approximately 5 years of age, offspring BMI percentile, FM%, BMI in the 95th percentile or higher, and FM% in the 95th percentile or higher.

Results

A total of 1325 pregnant women (mean [SD] age, 27.8 [6.2 years]; 322 [24.3%] Hispanic, 207 non-Hispanic Black [15.6%], and 713 [53.8%] non-Hispanic White), and 727 offspring with anthropometric data measured in childhood (mean [SD] age 4.81 [0.72] years, 48% female) were included. We identified the following 5 maternal metabolic subgroups: reference (438 participants), high HDL-C (355 participants), dyslipidemic-high triglycerides (182 participants), dyslipidemic-high FFA (234 participants), and insulin resistant (IR)-hyperglycemic (116 participants). Compared with the reference subgroup, women in the IR-hyperglycemic and dyslipidemic-high FFA subgroups had offspring with 4.27% (95% CI, 1.94-6.59) and 1.96% (95% CI, 0.45-3.47) greater FM% during childhood, respectively. There was a higher risk of high FM% among offspring of the IR-hyperglycemic (relative risk, 8.7; 95% CI, 2.7-27.8) and dyslipidemic-high FFA (relative risk, 3.4; 95% CI, 1.0-11.3) subgroups; this risk was of greater magnitude compared with prepregnancy obesity alone, GDM alone, or both conditions.

Conclusions and Relevance

In this cohort study, an unsupervised clustering approach revealed distinct metabolic subgroups of pregnant women. These subgroups exhibited differences in risk of offspring adiposity in early childhood. Such approaches have the potential to refine understanding of the in utero metabolic milieu, with utility for capturing variation in sociocultural, anthropometric, and biochemical risk factors for offspring adiposity.

Reducing bias in experimental ecology through directed acyclic graphs

Ecologists often rely on randomized control trials (RCTs) to quantify causal relationships in nature. Many of our foundational insights of ecological phenomena can be traced back to well‐designed experiments, and RCTs continue to provide valuable insights today. Although RCTs are often regarded as the “gold standard” for causal inference, it is important to recognize that they too rely on a set of causal assumptions that must be justified and met by the researcher to draw valid causal conclusions. We use key ecological examples to show how biases such as confounding, overcontrol, and collider bias can occur in experimental setups. In tandem, we highlight how such biases can be removed through the application of the structural causal model (SCM) framework. The SCM framework visualizes the causal structure of a system or process under study using directed acyclic graphs (DAGs) and subsequently applies a set of graphical rules to remove bias from both observational and experimental data. We show how DAGs can be applied across ecological experimental studies to ensure proper study design and statistical analysis, leading to more accurate causal estimates drawn from experimental data. Although causal conclusions drawn from RCTs are often taken at face value, ecologists are increasingly becoming aware that experimental approaches must be carefully designed and analyzed to avoid potential biases. By applying DAGs as a visual and conceptual tool, experimental ecologists can increasingly meet the causal assumptions required for valid causal inference.

What Happens In Utero Does Not Stay In Utero: a Review of Evidence for Prenatal Epigenetic Programming by Per- and Polyfluoroalkyl Substances (PFAS) in Infants, Children, and Adolescents

PURPOSE OF REVIEW

Review human literature on the relationship between prenatal exposure to per- and polyfluoroalkyl substances (PFAS) and epigenetic modifications in infants, children, and adolescents < 18 years of age.

RECENT FINDINGS

Eleven studies were identified, with study populations located in the U.S., Taiwan, Japan, and the Kingdom of Denmark. Many studies (n = 5) were cross-sectional, with PFAS exposure and epigenetic outcomes measured in the same tissue collected at delivery via cord blood or dried newborn blood spots. The other six studies were prospective, with prenatal PFAS measured on maternal blood during pregnancy and DNA methylation (DNAm) assessed in cord blood and childhood peripheral leukocytes (n = 1 study). Epigenetic marks of interest included global DNAm measures (LINE-1, Alu, and an ELISA-based method), candidate genes (IFG2, H19, and MEST), and epigenome-wide DNA methylation via array-based methods (Infinium 450 K and EPIC). Two studies using array-based methods employed discovery and validation paradigms, in which a small subset of loci (n = 6 and n = 4) were replicated in the discovery population. One site (TNXB) was a hit in two independent studies. Collectively, loci associated with PFAS were in regions involved in growth and development, lipid metabolism, and nutrient metabolism. There is moderate human evidence supporting associations of prenatal PFAS exposure on DNAm at birth, with one study suggesting sustained effects into childhood. Future studies are warranted to link PFAS-associated DNAm to health outcomes, as well as to investigate the role of other epigenetic marks such as hydroxymethylation, miRNA expression, and histone modifications.

Model selection in occupancy models: Inference versus prediction

Occupancy models are a vital tool for ecologists studying the patterns and drivers of species occurrence, but their use often involves selecting among models with different sets of occupancy and detection covariates. The information-theoretic approach, which employs information criteria such as Akaike's information criterion (AIC) is arguably the most popular approach for model selection in ecology and is often used for selecting occupancy models. However, the information-theoretic approach risks selecting models that produce inaccurate parameter estimates due to a phenomenon called collider bias, a type of confounding that can arise when adding explanatory variables to a model. Using simulations, we investigated the consequences of collider bias (using an illustrative example called M-bias) in the occupancy and detection processes of an occupancy model, and explored the implications for model selection using AIC and a common alternative, the Schwarz criterion (or Bayesian information criterion, BIC). We found that when M-bias was present in the occupancy process, AIC and BIC selected models that inaccurately estimated the effect of the focal occupancy covariate, while simultaneously producing more accurate predictions of the site-level occupancy probability than other models in the candidate set. In contrast, M-bias in the detection process did not impact the focal estimate; all models made accurate inferences, while the site-level predictions of the AIC/BIC-best model were slightly more accurate. Our results show that information criteria can be used to select occupancy covariates if the sole purpose of the model is prediction, but must be treated with more caution if the purpose is to understand how environmental variables affect occupancy. By contrast, detection covariates can usually be selected using information criteria regardless of the model's purpose. These findings illustrate the importance of distinguishing between the tasks of parameter inference and prediction in ecological modeling. Furthermore, our results underline concerns about the use of information criteria to compare different biological hypotheses in observational studies.

Chimpanzee pant-hoots encode individual information more reliably than group differences

Vocal learning, the ability to modify the acoustic structure of vocalizations based on social experience, is a fundamental feature of speech in humans (Homo sapiens). While vocal learning is common in taxa such as songbirds and whales, the vocal learning capacities of nonhuman primates appear more limited. Intriguingly, evidence for vocal learning has been reported in chimpanzees (Pan troglodytes), for example, in the form of regional variation ("dialects") in the "pant-hoot" calls. This suggests that some capacity for vocal learning may be an ancient feature of the Pan-Homo clade. Nonetheless, reported differences have been subtle, with intercommunity variation representing only a small portion of the total acoustic variation. To gain further insights into the extent of regional variation in chimpanzee vocalizations, we performed an analysis of pant-hoots from chimpanzees in the neighboring Kasekela and Mitumba communities at Gombe National Park, Tanzania, and the geographically distant Kanyawara community at Kibale National Park, Uganda. We did not find any statistically significant differences between the neighboring communities at Gombe or among geographically distant communities. Furthermore, we found differences among individuals in all communities. Hence, the variation in chimpanzee pant-hoots reflected individual differences, rather than group differences. Thus, we did not find evidence of dialects in this population, suggesting that extensive vocal learning emerged only after the lineages of Homo and Pan diverged.

Association of Early Norepinephrine Administration With 24-Hour Mortality Among Patients With Blunt Trauma and Hemorrhagic Shock

IMPORTANCE

Hemorrhagic shock is a common cause of preventable death after injury. Vasopressor administration for patients with blunt trauma and hemorrhagic shock is often discouraged.

OBJECTIVE

To evaluate the association of early norepinephrine administration with 24-hour mortality among patients with blunt trauma and hemorrhagic shock.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective, multicenter, observational cohort study used data from 3 registries in the US and France on all consecutive patients with blunt trauma from January 1, 2013, to December 31, 2018. Patients were alive on admission with hemorrhagic shock, defined by prehospital or admission systolic blood pressure less than 100 mm Hg and evidence of hemorrhage (ie, prehospital or resuscitation room transfusion of packed red blood cells, receipt of emergency treatment for hemorrhage control, transfusion of >10 units of packed red blood cells in the first 24 hours, or death from hemorrhage). Blunt trauma was defined as any exposure to nonpenetrating kinetic energy, collision, or deceleration. Statistical analysis was performed from January 15, 2021, to February 22, 2022.

EXPOSURE

Continuous administration of norepinephrine in the prehospital environment or resuscitation room prior to hemorrhage control, according to European guidelines.

MAIN OUTCOMES AND MEASURES

The primary outcome was 24-hour mortality, and the secondary outcome was in-hospital mortality. The average treatment effect (ATE) of early norepinephrine administration on 24-hour mortality was estimated according to the Rubin causal model. Inverse propensity score weighting and the doubly robust approach with 5 distinct analytical strategies were used to determine the ATE.

RESULTS

A total of 52 568 patients were screened for inclusion, and 2164 patients (1508 men [70%]; mean [SD] age, 46 [19] years; median Injury Severity Score, 29 [IQR, 17-36]) presented with acute hemorrhage and were included. A total of 1497 patients (69.1%) required emergency hemorrhage control, 128 (5.9%) received a prehospital transfusion of packed red blood cells, and 543 (25.0%) received a massive transfusion. Norepinephrine was administered to 1498 patients (69.2%). The 24-hour mortality rate was 17.8% (385 of 2164), and the in-hospital mortality rate was 35.6% (770 of 2164). None of the 5 analytical strategies suggested any statistically significant association between norepinephrine administration and 24-hour mortality, with ATEs ranging from -4.6 (95% CI, -11.9 to 2.7) to 2.1 (95% CI, -2.1 to 6.3), or between norepinephrine administration and in-hospital mortality, with ATEs ranging from -1.3 (95% CI, -9.5 to 6.9) to 5.3 (95% CI, -2.1 to 12.8).

CONCLUSIONS AND RELEVANCE

The findings of this study suggest that early norepinephrine infusion was not associated with 24-hour or in-hospital mortality among patients with blunt trauma and hemorrhagic shock. Randomized clinical trials that study the effect of early norepinephrine administration among patients with trauma and hypotension are warranted to further assess whether norepinephrine is safe for patients with hemorrhagic shock.

Using relative brain size as predictor variable: Serious pitfalls and solutions

There is a long‐standing interest in the effect of relative brain size on other life history variables in a comparative context. Historically, residuals have been used to calculate these effects, but more recently it has been recognized that regression on residuals is not good practice. Instead, absolute brain size and body size are included in a multiple regression, with the idea that this controls for allometry. I use a simple simulation to illustrate how a case in which brain size is a response variable differs from a case in which relative brain size is a predictor variable. I use the simulated data to test which modeling approach can estimate the underlying causal effects for each case. The results show that a multiple regression model with both body size and another variable as predictor variable and brain size as response variable work well. However, if relative brain size is a predictor variable, a multiple regression fails to correctly estimate the effect of body size. I propose the use of structural equation models to simultaneously estimate relative brain size and its effect on the third variable and discuss other potential methods.

Repeated Measures of Modified Rankin Scale Scores to Assess Functional Recovery From Stroke: AFFINITY Study Findings

Background

Function after acute stroke using the modified Rankin Scale (mRS) is usually assessed at a point in time. The analytical implications of serial mRS measurements to evaluate functional recovery over time is not completely understood. We compare repeated‐measures and single‐measure analyses of the mRS from a randomized clinical trial.

Methods and Results

Serial mRS data from AFFINITY (Assessment of Fluoxetine in Stroke Recovery), a double‐blind placebo randomized clinical trial of fluoxetine following stroke (n=1280) were analyzed to identify demographic and clinical associations with functional recovery (reduction in mRS) over 12 months. Associations were identified using single‐measure (day 365) and repeated‐measures (days 28, 90, 180, and 365) partial proportional odds logistic regression. Ninety‐five percent of participants experienced a reduction in mRS after 12 months. Functional recovery was associated with age at stroke <70 years; no prestroke history of diabetes, coronary heart disease, or ischemic stroke; prestroke history of depression, a relationship partner, living with others, independence, or paid employment; no fluoxetine intervention; ischemic stroke (compared with hemorrhagic); stroke treatment in Vietnam (compared with Australia or New Zealand); longer time since current stroke; and lower baseline National Institutes of Health Stroke Scale & Patient Health Questionnaire‐9 scores. Direction of associations was largely concordant between single‐measure and repeated‐measures models. Association strength and variance was generally smaller in the repeated‐measures model compared with the single‐measure model.

Conclusions

Repeated‐measures may improve trial precision in identifying trial associations and effects. Further repeated‐measures stroke analyses are required to prove methodological value.

Registration

URL: http://www.anzctr.org.au; Unique identifier: ACTRN12611000774921.

Characterization of Maternal Psychosocial Stress During Pregnancy: The Healthy Start Study

Objective:

To capture multidimensional maternal psychosocial stress using responses from the Edinburgh Postnatal Depression Scale (EPDS) and Cohen's Perceived Stress Scale (PSS) administered during pregnancy, and to identify sociodemographic, biological, and health behavioral correlates of the stress domains.

Methods:

Using data from 1,079 pregnant women, we implemented principal component analysis on EPDS and PSS responses and retained factors based on the Scree plot and Eigenvalues >1. We then used linear regression to identify perinatal correlates of each domain.

Results:

We identified three stress domains: “Feeling Overwhelmed,” “Anhedonia,” and “Lack of Control,” which accounted for 10.6% of variance in questionnaire responses. In multivariable analyses, household income ≤$70,000 (β = 0.21 confidence interval [95% CI: 0.05–0.39]), primiparity (0.36 [0.02–0.71]), inadequate (0.21 [0.04–0.39]) or excessive gestational weight gain (0.27 [0.11–0.42]), and Healthy Eating Index (HEI) score ≤57 (0.14 [0.00–0.28]) were associated with Feeling Overwhelmed. Older age (0.02 [0.00–0.03] per 1-year), Hispanic ethnicity (0.19 [0.00–0.38]), and HEI score ≤57 (0.15 [0.02–0.28]) were associated with Anhedonia. Non-Hispanic Black race/ethnicity (0.37 [0.10–0.63]), not having graduated from college (0.16 [−0.02 to 0.35]), having a partner born outside the United States (0.17 [−0.02 to 0.37]), household size of ≥5 persons (0.21 [−0.02 to 0.37]), receiving public assistance (0.18 [−0.02 to 0.37]), and prenatal smoking (0.32 [0.05–0.59]) were associated with Lack of Control.

Conclusions:

Three domains of maternal psychosocial stress during pregnancy (Feeling Overwhelmed, Anhedonia, and Lack of Control) were differentially related to sociodemographic, biological, and health behavioral characteristics that may be targets for interventions to ameliorate stress in pregnant women.

Clinical Trial Registry

: The Healthy Start study is registered as an observational study at clinicaltrials.gov (NCT #002273297).

Both prey and predator features predict the individual predation risk and survival of schooling prey

Predation is one of the main evolutionary drivers of social grouping. While it is well appreciated that predation risk is likely not shared equally among individuals within groups, its detailed quantification has remained difficult due to the speed of attacks and the highly dynamic nature of collective prey response. Here, using high-resolution tracking of solitary predators (Northern pike) hunting schooling fish (golden shiners), we not only provide insights into predator decision-making, but show which key spatial and kinematic features of predator and prey predict the risk of individuals to be targeted and to survive attacks. We found that pike tended to stealthily approach the largest groups, and were often already inside the school when launching their attack, making prey in this frontal ‘strike zone’ the most vulnerable to be targeted. From the prey’s perspective, those fish in central locations, but relatively far from, and less aligned with, neighbours, were most likely to be targeted. While the majority of attacks were successful (70%), targeted individuals that did manage to avoid being captured exhibited a higher maximum acceleration response just before the attack and were further away from the pike‘s head. Our results highlight the crucial interplay between predators’ attack strategy and response of prey underlying the predation risk within mobile animal groups.

Applications of conceptual models from lifecourse epidemiology in ecology and evolutionary biology

In ecology and evolutionary biology (EEB), the study of developmental plasticity seeks to understand ontogenetic processes underlying the phenotypes upon which natural selection acts. A central challenge to this inquiry is ascertaining a causal effect of the exposure on the manifestation of later-life phenotype due to the time elapsed between the two events. The exposure is a potential cause of the outcome-i.e. an environmental stimulus or experience. The later phenotype might be a behaviour, physiological condition, morphology or life-history trait. The latency period between the exposure and outcome complicates causal inference due to the inevitable occurrence of additional events that may affect the relationship of interest. Here, we describe six distinct but non-mutually exclusive conceptual models from the field of lifecourse epidemiology and discuss their applications to EEB research. The models include Critical Period with No Later Modifiers, Critical Period with Later Modifiers, Accumulation of Risk with Independent Risk Exposures, Accumulation of Risk with Risk Clustering, Accumulation of Risk with Chains of Risk and Accumulation of Risk with Trigger Effect. These models, which have been widely used to test causal hypotheses regarding the early origins of adult-onset disease in humans, are directly relevant to research on developmental plasticity in EEB.

Associations between Toxoplasma gondii infection and steroid hormone levels in spotted hyenas

Toxoplasma gondii is a common parasite that infects warm-blooded animals and influences host physiology. T. gondii is known to target the host's central nervous system, affecting circulating levels of steroid hormones, fear-related behaviors, and health, although these effects appear to vary among host taxa. Here, we investigated the relationship between T. gondii infection and levels of plasma testosterone and cortisol within a wild population of spotted hyenas (Crocutacrocuta, n = 109). In our analyses, we accounted for age and sex via stratified regression analyses. We detected a negative association between circulating plasma testosterone and T. gondii infection among female cubs and subadults as well as adult male hyenas. We found no associations between T. gondii infection and cortisol in any age class or sex group of hyenas. Our work adds to a growing body of literature by characterizing the relationship between T. gondii infection and physiology in a novel host in its natural habitat. In a broader context, our findings indicate that responses to infection vary with characteristics of the host and point to a clear need for additional studies and priorities for future work that include diverse taxa and ecological settings.

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Toxoplasma gondii infects diverse hosts and leads to differences in hormone levels.

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The relationship between T. gondii infection and host hormone response is mixed.

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We assessed if wild spotted hyena hormones differed by T. gondii infection.

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Testosterone was lower in infected female cub/subadult and adult males hyenas.

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Our results parallel laboratory findings but provide added realism of a wild animal.

Coevolution of relative brain size and life expectancy in parrots

Previous studies have demonstrated a correlation between longevity and brain size in a variety of taxa. Little research has been devoted to understanding this link in parrots; yet parrots are well-known for both their exceptionally long lives and cognitive complexity. We employed a large-scale comparative analysis that investigated the influence of brain size and life-history variables on longevity in parrots. Specifically, we addressed two hypotheses for evolutionary drivers of longevity: the cognitivebuffer hypothesis, which proposes that increased cognitive abilities enable longer lifespans, and the expensive brain hypothesis, which holds that increases in lifespan are caused by prolonged developmental time of, and increased parental investment in, large-brained offspring. We estimated life expectancy from detailed zoo records for 133 818 individuals across 244 parrot species. Using a principled Bayesian approach that addresses data uncertainty and imputation of missing values, we found a consistent correlation between relative brain size and life expectancy in parrots. This correlation was best explained by a direct effect of relative brain size. Notably, we found no effects of developmental time, clutch size or age at first reproduction. Our results suggest that selection for enhanced cognitive abilities in parrots has in turn promoted longer lifespans.

Matrilateral bias of grandparental investment in grandchildren persists despite the grandchildren's adverse early life experiences

Evolutionary theory predicts a downward flow of investment from older to younger generations, representing individual efforts to maximize inclusive fitness. Maternal grandparents and maternal grandmothers (MGMs) in particular consistently show the highest levels of investment (e.g. time, care and resources) in their grandchildren. Grandparental investment overall may depend on social and environmental conditions that affect the development of children and modify the benefits and costs of investment. Currently, the responses of grandparents to adverse early life experiences (AELEs) in their grandchildren are assessed from a perspective of increased investment to meet increased need. Here, we formulate an alternative prediction that AELEs may be associated with reduced grandparental investment, as they can reduce the reproductive value of the grandchildren. Moreover, we predicted that paternal grandparents react more strongly to AELEs compared to maternal grandparents because maternal kin should expend extra effort to invest in their descendants. Using population-based survey data for English and Welsh adolescents, we found evidence that the investment of maternal grandparents (MGMs in particular) in their grandchildren was unrelated to the grandchildren's AELEs, while paternal grandparents invested less in grandchildren who had experienced more AELEs. These findings seemed robust to measurement errors in AELEs and confounding due to omitted shared causes.

We should not necessarily expect positive relationships between biodiversity and ecosystem functioning in observational field data

Our current, empirical understanding of the relationship between biodiversity and ecosystem function is based on two information sources. First, controlled experiments which show generally positive relationships. Second, observational field data which show variable relationships. This latter source coupled with a lack of observed declines in local biodiversity has led to the argument that biodiversity-ecosystem functioning relationships may be uninformative for conservation and management. We review ecological theory and re-analyse several biodiversity datasets to argue that ecosystem function correlations with local diversity in observational field data are often difficult to interpret in the context of biodiversity-ecosystem function research. This occurs because biotic interactions filter species during community assembly which means that there can be a high biodiversity effect on functioning even with low observed local diversity. Our review indicates that we should not necessarily expect any specific relationship between local biodiversity and ecosystem function in observational field data. Rather, linking predictions from biodiversity-ecosystem function theory and experiments to observational field data requires considering the pool of species available during colonisation: the local species pool. We suggest that, even without local biodiversity declines, biodiversity loss at regional scales-which determines local species pools-may still negatively affect ecosystem functioning.