Depression and parenting: The need for improved intervention models

The impact of maternal depression on parenting is well established and there is a clear interaction between maternal depression and parenting that is predictive of child outcomes. The research on paternal depression is more limited but suggests the father’s mental health may be an independent risk factor for both parenting and child outcomes. There is insufficient evidence that treatment of depression alone – be it through pharmacological or psychological interventions – is able to substantially reduce the impact of depression on child outcomes. The evidence of interventions aimed at parenting and/or child outcomes in the context of depression is limited and the findings that are available are mixed

Parenting stress, maternal depression and child mental health in a Melbourne cohort before and during the COVID‐19 pandemic

Aim This paper aims to examine the maternal and child mental health and parenting outcomes in the context of COVID-19 pandemic conditions using a sample from Melbourne, Australia – a city exposed to one of the longest lockdowns world-wide in response to the pandemic. Methods This study utilises observational data from a prospective, pregnancy cohort, Mercy Pregnancy Emotional Wellbeing Study and includes 468 women and their children followed up in Melbourne to 3–4 years postpartum pre-COVID pandemic and compared to those followed up during the COVID-19 pandemic. Results When compared to mothers followed up at 3–4 years postpartum pre-pandemic, those followed up during the COVID-19 pandemic showed higher depressive symptoms with a steep incline in their symptom trajectory (EMMdifference = 1.72, Bonferroni-corrected P < 0.01, d = 0.35) and had a three times higher risk of scoring 13 or above on the EPDS (aRR = 3.22, Bonferroni-corrected P < 0.01). Although this increase was not associated with the variation in the duration of exposure to pandemic conditions, the steep increase in depressive symptoms was more pronounced in those with pre-existing depressive disorders. There was no difference in parenting stress or adjusted childhood mental health symptoms or disorder. Conclusions Our findings highlight the vulnerability of those with pre-existing clinical mental health disorders and the need for adequate clinical care for this vulnerable group. Equally, our study indicates the possibility that parenting and early childhood mental health outcomes, at least in the short term, may be resilient

Rurality as a predictor of perinatal mental health and well‐being in an Australian cohort

Objective Perinatal emotional well-being is more than the presence or absence of depressive and anxiety disorders; it encompasses a wide range of factors that contribute to emotional well-being. This study compares perinatal well-being between women living in metropolitan and rural regions. Design Prospective, longitudinal cohort. Participants/setting Eight hundred and six women from Victoria and Western Australia recruited before 20 weeks of pregnancy and followed up to 12 months postpartum. Main outcome measures Rurality was assessed using the Modified Monash Model (MM Model) with 578 in metropolitan cities MM1, 185 in regional and large rural towns MM2-MM3 and 43 in rural to remote MM4-MM7. The Structured Clinical Interview for DSM-IV (SCID-IV) was administered at recruitment to assess depression, and symptoms of depression and anxiety were measured using the Edinburgh Post-natal Depression Scale and the State and Trait Anxiety Scale, respectively. Other measures included stressful events, diet, exercise, partner support, parenting and sleep. Results The prevalence of depressive disorders did not differ across rurality. There was also no difference in breastfeeding cessation, exercise, sleep or partner support. Women living in rural communities and who also had depression reported significantly higher parenting stress than metropolitan women and lower access to parenting activities. Conclusions Our study suggests while many of the challenges of the perinatal period were shared between women in all areas, there were important differences in parenting stress and access to activities. Furthermore, these findings suggest that guidelines and interventions designed for perinatal mental health should consider rurality

Biomass burning at Cape Grim: exploring photochemistry using multi-scale modelling

We have tested the ability of a high-resolution chemical transport model (CTM) to reproduce biomass burning (BB) plume strikes and ozone (O3) enhancements observed at Cape Grim in Tasmania, Australia, from the Robbins Island fire. The CTM has also been used to explore the contribution of near-field BB emissions and background sources to O3 observations under conditions of complex meteorology. Using atmospheric observations, we have tested model sensitivity to meteorology, BB emission factors (EFs) corresponding to low, medium, and high modified combustion efficiency (MCE), and spatial variability. The use of two different meteorological models (TAPM–CTM and CCAM–CTM) varied the first (BB1) plume strike time by up to 15 h and the duration of impact between 12 and 36 h, and it varied the second (BB2) plume duration between 50 and 57 h. Meteorology also had a large impact on simulated O3, with one model (TAPM–CTM) simulating four periods of O3 enhancement, while the other model (CCAM) simulating only one period. Varying the BB EFs, which in turn varied the non-methane organic compound (NMOC) ∕ oxides of nitrogen (NOx) ratio, had a strongly non-linear impact on simulated O3 concentration, with either destruction or production of O3 predicted in different simulations. As shown in previous work (Lawson et al., 2015), minor rainfall events have the potential to significantly alter EF due to changes in combustion processes. Models that assume fixed EF for O3 precursor species in an environment with temporally or spatially variable EF may be unable to simulate the behaviour of important species such as O3. TAPM–CTM is used to further explore the contribution of the Robbins Island fire to the observed O3 enhancements during BB1 and BB2. Overall, TAPM–CTM suggests that the dominant source of O3 observed at Cape Grim was aged urban air (age  = 2 days), with a contribution of O3 formed from local BB emissions. This work shows the importance of assessing model sensitivity to meteorology and EF and the large impact these variables can have in particular on simulated destruction or production of O3 in regional atmospheric chemistry simulations. This work also shows the importance of using models to elucidate the contribution from different sources to atmospheric composition, where this is difficult using observations alone

On the vulnerability of iris-based systems to a software attack based on a genetic algorithm

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-33275-3_14Proceedings of 17th Iberoamerican Congress, CIARP 2012, Buenos Aires, ArgentinaThe vulnerabilities of a standard iris verification system to a novel indirect attack based on a binary genetic algorithm are studied. The experiments are carried out on the iris subcorpus of the publicly available BioSecure DB. The attack has shown a remarkable performance, thus proving the lack of robustness of the tested system to this type of threat. Furthermore, the consistency of the bits of the iris code is analysed, and a second working scenario discarding the fragile bits is then tested as a possible countermeasure against the proposed attack.This work has been partially supported by projects Contexts (S2009/TIC-1485) from CAM, Bio-Challenge (TEC2009-11186) from Spanish MICINN, TABULA RASA (FP7-ICT-257289) and BEAT (FP7-SEC-284989) from EU, and Cátedra UAM-Telefónica

Infant sleep and anxiety disorders in early childhood: Findings from an Australian pregnancy cohort study

Emphasis on continuous infant sleep overnight may be driven by parental concern of risk to child mental health outcomes. The Mercy Pregnancy and Emotional Wellbeing Study (MPEWS) examined whether infant sleep at 6 and 12 months postpartum predicts anxiety disorders at 2–4 years, and whether this is moderated by maternal depression, active physical comforting (APC) or maternal cognitions about infant sleep. Data included 349 women and infants. Infant sleep was measured using the Brief Infant Sleep Questionnaire and child anxiety disorders by the Preschool Age Psychiatric Assessment. The risk of developing generalised anxiety or social phobia disorders at 3–4 years was reduced by 42% (p = 0.001) and 31% (p = 0.001), respectively, for a one standard deviation increase in total sleep at 12 months. No other infant sleep outcomes were associated. Maternal depression, APC and cognitions about infant sleep did not significantly moderate these relationships. Focus may need to be on total infant sleep, rather than when sleep is achieved. Highlights: To assess whether infant sleep outcomes (i.e., frequency of nocturnal wakes; nocturnal wakefulness and total sleep per day) at 6 and 12 months predict early childhood anxiety disorders at 3–4 years of age. Maternally reported infant sleep outcomes were not associated with the risk of developing early childhood anxiety disorders at 3–4 years. It may be total infant sleep, irrespective of when sleep occurs or night waking and, independently, active physical comforting that requires further investigation

Gridded global surface ozone metrics for atmospheric chemistry model evaluation

The concentration of ozone at the Earth's surface is measured at many locations across the globe for the purposes of air quality monitoring and atmospheric chemistry research. We have brought together all publicly available surface ozone observations from online databases from the modern era to build a consistent data set for the evaluation of chemical transport and chemistry-climate (Earth System) models for projects such as the Chemistry-Climate Model Initiative and Aer-Chem-MIP. From a total data set of approximately 6600 sites and 500 million hourly observations from 1971-2015, approximately 2200 sites and 200 million hourly observations pass screening as high-quality sites in regionally representative locations that are appropriate for use in global model evaluation. There is generally good data volume since the start of air quality monitoring networks in 1990 through 2013. Ozone observations are biased heavily toward North America and Europe with sparse coverage over the rest of the globe. This data set is made available for the purposes of model evaluation as a set of gridded metrics intended to describe the distribution of ozone concentrations on monthly and annual timescales. Metrics include the moments of the distribution, percentiles, maximum daily 8-hour average (MDA8), sum of means over 35 ppb (daily maximum 8-h; SOMO35), accumulated ozone exposure above a threshold of 40 ppbv (AOT40), and metrics related to air quality regulatory thresholds. Gridded data sets are stored as netCDF-4 files and are available to download from the British Atmospheric Data Centre (doi:10.5285/08fbe63d-fa6d-4a7a-b952-5932e3ab0452). We provide recommendations to the ozone measurement community regarding improving metadata reporting to simplify ongoing and future efforts in working with ozone data from disparate networks in a consistent manner

Towards a universal “baseline” characterisation of air masses for high- and low-altitude observing stations using Radon-222

We demonstrate the ability of atmospheric radon concentrations to reliably and unambiguously identify local and remote terrestrial influences on an air mass, and thereby the potential for alteration of trace gas composition by anthropogenic and biogenic processes. Based on high accuracy (lower limit of detection 10–40 mBq m–3), high temporal resolution (hourly) measurements of atmospheric radon concentration we describe, apply and evaluate a simple two-step method for identifying and characterising constituent mole fractions in baseline air. The technique involves selecting a radon-based threshold concentration to identify the “cleanest” (least terrestrially influenced) air masses, and then performing an outlier removal step based on the distribution of constituent mole fractions in the identified clean air masses. The efficacy of this baseline selection technique is tested at three contrasting WMO GAW stations: Cape Grim (a coastal low-altitude site), Mauna Loa (a remote high-altitude island site), and Jungfraujoch (a continental high-altitude site). At Cape Grim and Mauna Loa the two-step method is at least as effective as more complicated methods employed to characterise baseline conditions, some involving up to nine steps. While it is demonstrated that Jungfraujoch air masses rarely meet the baseline criteria of the more remote sites, a selection method based on a variable monthly radon threshold is shown to produce credible “near baseline” characteristics. The seasonal peak-to-peak amplitude of recent monthly baseline CO2 mole fraction deviations from the long-term trend at Cape Grim, Mauna Loa and Jungfraujoch are estimated to be 1.1, 6.0 and 8.1 ppm, respectively

Comparison of some Reduced Representation Approximations

In the field of numerical approximation, specialists considering highly complex problems have recently proposed various ways to simplify their underlying problems. In this field, depending on the problem they were tackling and the community that are at work, different approaches have been developed with some success and have even gained some maturity, the applications can now be applied to information analysis or for numerical simulation of PDE's. At this point, a crossed analysis and effort for understanding the similarities and the differences between these approaches that found their starting points in different backgrounds is of interest. It is the purpose of this paper to contribute to this effort by comparing some constructive reduced representations of complex functions. We present here in full details the Adaptive Cross Approximation (ACA) and the Empirical Interpolation Method (EIM) together with other approaches that enter in the same category

Current estimates of biogenic emissions from Eucalypts uncertain for Southeast Australia

The biogenic emissions of isoprene and monoterpenes are one of the main drivers of atmospheric photochemistry, including oxidant and secondary organic aerosol production. In this paper, the emission rates of isoprene and monoterpenes from Australian vegetation are investigated for the first time using the Model of Emissions of Gases and Aerosols from Nature version 2.1 (MEGANv2.1); the CSIRO chemical transport model; and atmospheric observations of isoprene, monoterpenes and isoprene oxidation products (methacrolein and methyl vinyl ketone). Observations from four field campaigns during three different seasons are used, covering urban, coastal suburban and inland forest areas. The observed concentrations of isoprene and monoterpenes were of a broadly similar magnitude, which may indicate that southeast Australia holds an unusual position where neither chemical species dominates. The model results overestimate the observed atmospheric concentrations of isoprene (up to a factor of 6) and underestimate the monoterpene concentrations (up to a factor of 4). This may occur because the emission rates currently used in MEGANv2.1 for Australia are drawn mainly from young eucalypt trees (\u3c 7 years), which may emit more isoprene than adult trees. There is no single increase/decrease factor for the emissions which suits all seasons and conditions studied. There is a need for further field measurements of in situ isoprene and monoterpene emission fluxes in Australia