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Studies have reported mixed findings regarding the impact of the coronavirus disease 2019 (COVID-19) pandemic on pregnant women and birth outcomes. This study used a quasi-experimental design to account for potential confounding by sociodemographic characteristics.
Data were drawn from 16 prenatal cohorts participating in the Environmental influences on Child Health Outcomes (ECHO) program. Women exposed to the pandemic (delivered between 12 March 2020 and 30 May 2021) (n = 501) were propensity-score matched on maternal age, race and ethnicity, and child assigned sex at birth with 501 women who delivered before 11 March 2020. Participants reported on perceived stress, depressive symptoms, sedentary behavior, and emotional support during pregnancy. Infant gestational age (GA) at birth and birthweight were gathered from medical record abstraction or maternal report.
After adjusting for propensity matching and covariates (maternal education, public assistance, employment status, prepregnancy body mass index), results showed a small effect of pandemic exposure on shorter GA at birth, but no effect on birthweight adjusted for GA. Women who were pregnant during the pandemic reported higher levels of prenatal stress and depressive symptoms, but neither mediated the association between pandemic exposure and GA. Sedentary behavior and emotional support were each associated with prenatal stress and depressive symptoms in opposite directions, but no moderation effects were revealed.
There was no strong evidence for an association between pandemic exposure and adverse birth outcomes. Furthermore, results highlight the importance of reducing maternal sedentary behavior and encouraging emotional support for optimizing maternal health regardless of pandemic conditions.
Fjord systems are transition zones between land and sea, resulting in complex and dynamic environments. They are of particular interest in the Arctic as they harbour ecosystems inhabited by a rich range of species and provide many societal benefits. The key drivers of change in the European Arctic (i.e., Greenland, Svalbard, and Northern Norway) fjord socio-ecological systems are reviewed here, structured into five categories: cryosphere (sea ice, glacier mass balance, and glacial and riverine discharge), physics (seawater temperature, salinity, and light), chemistry (carbonate system, nutrients), biology (primary production, biomass, and species richness), and social (governance, tourism, and fisheries). The data available for the past and present state of these drivers, as well as future model projections, are analysed in a companion paper. Changes to the two drivers at the base of most interactions within fjords, seawater temperature and glacier mass balance, will have the most significant and profound consequences on the future of European Arctic fjords. This is because even though governance may be effective at mitigating/adapting to local disruptions caused by the changing climate, there is possibly nothing that can be done to halt the melting of glaciers, the warming of fjord waters, and all of the downstream consequences that these two changes will have. This review provides the first transdisciplinary synthesis of the interactions between the drivers of change within Arctic fjord socio-ecological systems. Knowledge of what these drivers of change are, and how they interact with one another, should provide more expedient focus for future research on the needs of adapting to the changing Arctic.
Assistive forces transmitted from wearable robots to the robot’s users are often defined by controllers that rely on the accurate estimation of the human posture. The compliant nature of the human–robot interface can negatively affect the robot’s ability to estimate the posture. In this article, we present a novel algorithm that uses machine learning to correct these errors in posture estimation. For that, we recorded motion capture data and robot performance data from a group of participants (n = 8; 4 females) who walked on a treadmill while wearing a wearable robot, the Myosuit. Participants walked on level ground at various gait speeds and levels of support from the Myosuit. We used optical motion capture data to measure the relative displacement between the person and the Myosuit. We then combined this data with data derived from the robot to train a model, using a grading boosting algorithm (XGBoost), that corrected for the mechanical compliance errors in posture estimation. For the Myosuit controller, we were particularly interested in the angle of the thigh segment. Using our algorithm, the estimated thigh segment’s angle RMS error was reduced from 6.3° (2.3°) to 2.5° (1.0°), mean (standard deviation). The average maximum error was reduced from 13.1° (4.9°) to 5.9° (2.1°). These improvements in posture estimation were observed for all of the considered assistance force levels and walking speeds. This suggests that ML-based algorithms provide a promising opportunity to be used in combination with wearable-robot sensors for an accurate user posture estimation.
Vector-borne parasites are important ecological drivers influencing life-history evolution in birds by increasing host mortality or susceptibility to new diseases. Therefore, understanding why vulnerability to infection varies within a host clade is a crucial task for conservation biology and for understanding macroecological life-history patterns. Here, we studied the relationship of avian life-history traits and climate on the prevalence of Plasmodium and Parahaemoproteus parasites. We sampled 3569 individual birds belonging to 53 species of the family Thraupidae. Individuals were captured from 2007 to 2018 at 92 locations. We created 2 phylogenetic generalized least-squares models with Plasmodium and Parahaemoproteus prevalence as our response variables, and with the following predictor variables: climate PC1, climate PC2, body size, mixed-species flock participation, incubation period, migration, nest height, foraging height, forest cover, and diet. We found that Parahaemoproteus and Plasmodium prevalence was higher in species inhabiting open habitats. Tanager species with longer incubation periods had higher Parahaemoproteus prevalence as well, and we hypothesize that these longer incubation periods overlap with maximum vector abundances, resulting in a higher probability of infection among adult hosts during their incubation period and among chicks. Lastly, we found that Plasmodium prevalence was higher in species without migratory behaviour, with mixed-species flock participation, and with an omnivorous or animal-derived diet. We discuss the consequences of higher infection prevalence in relation to life-history traits in tanagers.
In this research note, we introduce congressbr, an R package for retrieving data from the Brazilian houses of legislature. The package contains easy-to-use functions that allow researchers to query the Application Programming Interfaces of Brazil’s Chamber of Deputies and the Federal Senate, perform cleaning data operations, and store information in a format convenient for future analyses, making a previously difficult task fast and convenient. Congressbr downloads data on legislators, submitted and ratified law proposals, Senate and Chamber commissions, and other information of interest to social scientists across various fields. We outline the main features of the package and demonstrate its use with practical examples.
This work applies stereometric parameters and fractal theory to characterize the structural complexity of the 3D surface roughness of Anacardium occidentale L. leaf using atomic force microscopy (AFM) measurements. Surface roughness was studied by AFM in tapping mode, in air, on square areas of 6,400 and 10,000 μm2. The stereometric analyses using MountainsMap Premium and WSXM software provided detailed information on the 3D surface topography of the samples. These data showed that the morphology of the abaxial and adaxial side of the cashew leaf is different, which was also observed in relation to their microtextures. Fractal analysis showed that the adaxial and abaxial sides have strong microtexture homogeneity, but the adaxial side presented higher surface entropy. These results show that image processing associated with fractal theory can be an indispensable tool for identifying plant species by their leaves because this species has singularities on each side of the leaf.
Whether monozygotic (MZ) and dizygotic (DZ) twins differ from each other in a variety of phenotypes is important for genetic twin modeling and for inferences made from twin studies in general. We analyzed whether there were differences in individual, maternal and paternal education between MZ and DZ twins in a large pooled dataset. Information was gathered on individual education for 218,362 adult twins from 27 twin cohorts (53% females; 39% MZ twins), and on maternal and paternal education for 147,315 and 143,056 twins respectively, from 28 twin cohorts (52% females; 38% MZ twins). Together, we had information on individual or parental education from 42 twin cohorts representing 19 countries. The original education classifications were transformed to education years and analyzed using linear regression models. Overall, MZ males had 0.26 (95% CI [0.21, 0.31]) years and MZ females 0.17 (95% CI [0.12, 0.21]) years longer education than DZ twins. The zygosity difference became smaller in more recent birth cohorts for both males and females. Parental education was somewhat longer for fathers of DZ twins in cohorts born in 1990–1999 (0.16 years, 95% CI [0.08, 0.25]) and 2000 or later (0.11 years, 95% CI [0.00, 0.22]), compared with fathers of MZ twins. The results show that the years of both individual and parental education are largely similar in MZ and DZ twins. We suggest that the socio-economic differences between MZ and DZ twins are so small that inferences based upon genetic modeling of twin data are not affected.
A trend toward greater body size in dizygotic (DZ) than in monozygotic (MZ) twins has been suggested by some but not all studies, and this difference may also vary by age. We analyzed zygosity differences in mean values and variances of height and body mass index (BMI) among male and female twins from infancy to old age. Data were derived from an international database of 54 twin cohorts participating in the COllaborative project of Development of Anthropometrical measures in Twins (CODATwins), and included 842,951 height and BMI measurements from twins aged 1 to 102 years. The results showed that DZ twins were consistently taller than MZ twins, with differences of up to 2.0 cm in childhood and adolescence and up to 0.9 cm in adulthood. Similarly, a greater mean BMI of up to 0.3 kg/m2 in childhood and adolescence and up to 0.2 kg/m2 in adulthood was observed in DZ twins, although the pattern was less consistent. DZ twins presented up to 1.7% greater height and 1.9% greater BMI than MZ twins; these percentage differences were largest in middle and late childhood and decreased with age in both sexes. The variance of height was similar in MZ and DZ twins at most ages. In contrast, the variance of BMI was significantly higher in DZ than in MZ twins, particularly in childhood. In conclusion, DZ twins were generally taller and had greater BMI than MZ twins, but the differences decreased with age in both sexes.
Recent studies suggest that sand can serve as a vehicle for exposure of humans to pathogens at beach sites, resulting in increased health risks. Sampling for microorganisms in sand should therefore be considered for inclusion in regulatory programmes aimed at protecting recreational beach users from infectious disease. Here, we review the literature on pathogen levels in beach sand, and their potential for affecting human health. In an effort to provide specific recommendations for sand sampling programmes, we outline published guidelines for beach monitoring programmes, which are currently focused exclusively on measuring microbial levels in water. We also provide background on spatial distribution and temporal characteristics of microbes in sand, as these factors influence sampling programmes. First steps toward establishing a sand sampling programme include identifying appropriate beach sites and use of initial sanitary assessments to refine site selection. A tiered approach is recommended for monitoring. This approach would include the analysis of samples from many sites for faecal indicator organisms and other conventional analytes, while testing for specific pathogens and unconventional indicators is reserved for high-risk sites. Given the diversity of microbes found in sand, studies are urgently needed to identify the most significant aetiological agent of disease and to relate microbial measurements in sand to human health risk.
For over 100 years, the genetics of human anthropometric traits has attracted scientific interest. In particular, height and body mass index (BMI, calculated as kg/m2) have been under intensive genetic research. However, it is still largely unknown whether and how heritability estimates vary between human populations. Opportunities to address this question have increased recently because of the establishment of many new twin cohorts and the increasing accumulation of data in established twin cohorts. We started a new research project to analyze systematically (1) the variation of heritability estimates of height, BMI and their trajectories over the life course between birth cohorts, ethnicities and countries, and (2) to study the effects of birth-related factors, education and smoking on these anthropometric traits and whether these effects vary between twin cohorts. We identified 67 twin projects, including both monozygotic (MZ) and dizygotic (DZ) twins, using various sources. We asked for individual level data on height and weight including repeated measurements, birth related traits, background variables, education and smoking. By the end of 2014, 48 projects participated. Together, we have 893,458 height and weight measures (52% females) from 434,723 twin individuals, including 201,192 complete twin pairs (40% monozygotic, 40% same-sex dizygotic and 20% opposite-sex dizygotic) representing 22 countries. This project demonstrates that large-scale international twin studies are feasible and can promote the use of existing data for novel research purposes.