Paediatrics (RCH) - Research Publications
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ItemOn the use of multiple imputation to address data missing by design as well as unintended missing data in case-cohort studies with a binary endpoint(BMC, 2023-12-07)BACKGROUND: Case-cohort studies are conducted within cohort studies, with the defining feature that collection of exposure data is limited to a subset of the cohort, leading to a large proportion of missing data by design. Standard analysis uses inverse probability weighting (IPW) to address this intended missing data, but little research has been conducted into how best to perform analysis when there is also unintended missingness. Multiple imputation (MI) has become a default standard for handling unintended missingness and is typically used in combination with IPW to handle the intended missingness due to the case-control sampling. Alternatively, MI could be used to handle both the intended and unintended missingness. While the performance of an MI-only approach has been investigated in the context of a case-cohort study with a time-to-event outcome, it is unclear how this approach performs with a binary outcome. METHODS: We conducted a simulation study to assess and compare the performance of approaches using only MI, only IPW, and a combination of MI and IPW, for handling intended and unintended missingness in the case-cohort setting. We also applied the approaches to a case study. RESULTS: Our results show that the combined approach is approximately unbiased for estimation of the exposure effect when the sample size is large, and was the least biased with small sample sizes, while MI-only and IPW-only exhibited larger biases in both sample size settings. CONCLUSIONS: These findings suggest that a combined MI/IPW approach should be preferred to handle intended and unintended missing data in case-cohort studies with binary outcomes.
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ItemNo Preview AvailableEmotional symptoms and inflammatory biomarkers in childhood: Associations in two Australian birth cohorts(Elsevier, 2024-01-01)BACKGROUND: An increasing body of evidence supports associations between inflammation and mental health difficulties, but the onset and directionality of these relationships are unclear. METHODS: Data sources: Barwon Infant Study (BIS; n = 500 4-year-olds) and Longitudinal Study of Australian Children (LSAC; n = 1099 10-13-year-olds). MEASURES: Strengths and Difficulties Questionnaire emotional symptoms at 4, 10-11 and 12-13 years, and circulating levels of two inflammatory biomarkers, high-sensitivity C-reactive protein (hsCRP) and glycoprotein acetyls (GlycA), at 4 and 11-12 years. ANALYSIS: Adjusted quantile regression models examining cross-sectional associations between emotional symptoms and inflammation in 4-year-olds (BIS), and cross-lagged associations in 10-13-year-olds (LSAC). RESULTS: We identified a small association between higher emotional symptoms at 10-11 years and higher GlycA levels a year later (standardised coefficient β = 0.09; 95%CI: 0.02 to 0.15). Sex-stratified analyses revealed this association was stronger for boys (β = 0.13; 95%CI: 0.04 to 0.21) than girls (β = 0.01; 95%CI: -0.09 to 0.11). These associations were not observed for hsCRP. There was little evidence of an association between higher GlycA or hsCRP at 11-12 years and emotional symptoms a year later, or cross-sectional associations between emotional symptoms and hsCRP or GlycA at 4 years. LIMITATIONS: A single time-point of biomarker collection in late childhood precluded adjustment for baseline inflammatory biomarkers. CONCLUSIONS: Our results support the direction of association from emotional symptoms to inflammation in late childhood, with potential sex differences. This adds to the body of evidence that addressing emotional symptoms in childhood is a major priority in optimising overall health throughout the life course.
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ItemCharacteristics and outcomes of children receiving intensive care therapy within 12 hours following a medical emergency team event(AUSTRALASIAN MED PUBL CO LTD, 2021-09)Objectives: To describe characteristics and outcomes of children requiring intensive care therapy (ICT) within 12 hours following a medical emergency team (MET) event. Design: Retrospective cohort study. Setting: Quaternary paediatric hospital. Patients: Children experiencing a MET event. Measurements and main results: Between July 2017 and March 2019, 890 MET events occurred in 566 patients over 631 admissions. Admission to intensive care followed 183/890 (21%) MET events. 76/183 (42%) patients required ICT, defined as positive pressure ventilation or vasoactive support in intensive care, within 12 hours. Older children had a lower risk of requiring ICT than infants aged < 1 year (age 1-5 years [risk difference, -6.4%; 95% CI, -11% to -1.6%; P = 0.01] v age > 5 years [risk difference, -8.0%; 95% CI, -12% to -3.8%; P < 0.001]), while experiencing a critical event increased this risk (risk difference, 16%; 95% CI, 3.3-29%; P = 0.01). The duration of respiratory support and intensive care length of stay was approximately double in patients requiring ICT (ratio of geometric means, 2.0 [95% CI, 1.4-3.0] v 2.1 [95% CI, 1.5-2.8]; P < 0.001) and the intensive care mortality increased (risk difference, 9.6%; 95% CI, 2.4-17%; P = 0.01). Heart rate, oxygen saturation and respiratory rate were the most commonly measured vital signs in the 6 hours before the MET event. Conclusions: Approximately one-fifth of MET events resulted in intensive care admission and nearly half of these required ICT within 12 hours. This group had greater duration of respiratory support, intensive care and hospital length of stay, and higher mortality. Age < 1 year and a critical event increased the risk of ICT.
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ItemNo Preview AvailableAssumptions and analysis planning in studies with missing data in multiple variables: moving beyond the MCAR/MAR/MNAR classification(OXFORD UNIV PRESS, 2023-08-02)Researchers faced with incomplete data are encouraged to consider whether their data are 'missing completely at random' (MCAR), 'missing at random' (MAR) or 'missing not at random' (MNAR) when planning their analysis. However, there are two major problems with this classification as originally defined by Rubin in the 1970s. First, when there are missing data in multiple variables, the plausibility of the MAR assumption is difficult to assess using substantive knowledge and is more stringent than is generally appreciated. Second, although MCAR and MAR are sufficient conditions for consistent estimation with specific methods, they are not necessary conditions and therefore this categorization does not directly determine the best approach for handling the missing data in an analysis. How best to handle missing data depends on the assumed causal relationships between variables and their missingness, and what these relationships imply in terms of the 'recoverability' of the target estimand (the population parameter that encodes the answer to the underlying research question). Recoverability is defined as whether the estimand can be consistently estimated from the patterns and associations in the observed data without needing to invoke external information on the extent to which the distribution of missing values might differ from that of observed values. In this manuscript we outline an approach for deciding which method to use to handle multivariable missing data in an analysis, using directed acyclic graphs to depict missingness assumptions and determining the implications in terms of recoverability of the target estimand.
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ItemNo Preview AvailableMaternal oxidative stress during pregnancy associated with emotional and behavioural problems in early childhood: implications for foetal programming(SPRINGERNATURE, 2023-09)Childhood mental disorders, including emotional and behavioural problems (EBP) are increasingly prevalent. Higher maternal oxidative stress (OS) during pregnancy (matOSpreg) is linked to offspring mental disorders. Environmental factors contribute to matOSpreg. However, the role of matOSpreg in childhood EBP is unclear. We investigated the associations between (i) matOSpreg and offspring EBP; (ii) social and prenatal environmental factors and matOSpreg; and (iii) social and prenatal factors and childhood EBP and evaluated whether matOSpreg mediated these associations. Maternal urinary OS biomarkers, 8-hydroxyguanosine (8-OHGua; an oxidative RNA damage marker) and 8-hydroxy-2'-deoxyguanosine (8-OHdG; an oxidative DNA damage marker), at 36 weeks of pregnancy were quantified by liquid chromatography-mass spectrometry in a population-derived birth cohort, Barwon Infant Study (n = 1074 mother-infant pairs). Social and prenatal environmental factors were collected by mother-reported questionnaires. Offspring total EBP was measured by Child Behavior Checklist Total Problems T-scores at age two (n = 675) and Strengths and Difficulties Questionnaire Total Difficulties score at age four (n = 791). Prospective associations were examined by multivariable regression analyses adjusted for covariates. Mediation effects were evaluated using counterfactual-based mediation analysis. Higher maternal urinary 8-OHGua at 36 weeks (mat8-OHGua36w) was associated with greater offspring total EBP at age four (β = 0.38, 95% CI (0.07, 0.69), P = 0.02) and age two (β = 0.62, 95% CI (-0.06, 1.30), P = 0.07). Weaker evidence of association was detected for 8-OHdG. Five early-life factors were associated with both mat8-OHGua36w and childhood EBP (P-range < 0.001-0.05), including lower maternal education, socioeconomic disadvantage and prenatal tobacco smoking. These risk factor-childhood EBP associations were partly mediated by higher mat8-OHGua36w (P-range = 0.01-0.05). Higher matOSpreg, particularly oxidant RNA damage, is associated with later offspring EBP. Effects of some social and prenatal lifestyle factors on childhood EBP were partly mediated by matOSpreg. Future studies are warranted to further elucidate the role of early-life oxidant damage in childhood EBP.
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ItemNo Preview AvailableThe forgotten girls: the state of evidence for health interventions for pregnant adolescents and their newborns in low-income and middle-income countries(Elsevier, 2023-10)Every year, an estimated 21 million girls aged 15-19 years become pregnant in low-income and middle-income countries (LMICs). Policy responses have focused on reducing the adolescent birth rate whereas efforts to support pregnant adolescents have developed more slowly. We did a systematic review of interventions addressing any health-related outcome for pregnant adolescents and their newborn babies in LMICs and mapped its results to a framework describing high-quality health systems for pregnant adolescents. Although we identified some promising interventions, such as micronutrient supplementation, conditional cash transfers, and well facilitated group care, most studies were at high risk of bias and there were substantial gaps in evidence. These included major gaps in delivery, abortion, and postnatal care, and mental health, violence, and substance misuse-related outcomes. We recommend that the fields of adolescent, maternal, and sexual and reproductive health collaborate to develop more adolescent-inclusive maternal health care and research, and specific interventions for pregnant adolescents. We outline steps to develop high-quality, evidence-based care for the millions of pregnant adolescents and their newborns who currently do not receive this.
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ItemParental personality and early life ecology: a prospective cohort study from preconception to postpartum(NATURE PORTFOLIO, 2023-02-27)Personality reliably predicts life outcomes ranging from social and material resources to mental health and interpersonal capacities. However, little is known about the potential intergenerational impact of parent personality prior to offspring conception on family resources and child development across the first thousand days of life. We analysed data from the Victorian Intergenerational Health Cohort Study (665 parents, 1030 infants; est. 1992), a two-generation study with prospective assessment of preconception background factors in parental adolescence, preconception personality traits in young adulthood (agreeableness, conscientiousness, emotional stability, extraversion, and openness), and multiple parental resources and infant characteristics in pregnancy and after the birth of their child. After adjusting for pre-exposure confounders, both maternal and paternal preconception personality traits were associated with numerous parental resources and attributes in pregnancy and postpartum, as well as with infant biobehavioural characteristics. Effect sizes ranged from small to moderate when considering parent personality traits as continuous exposures, and from small to large when considering personality traits as binary exposures. Young adult personality, well before offspring conception, is associated with the perinatal household social and financial context, parental mental health, parenting style and self-efficacy, and temperamental characteristics of offspring. These are pivotal aspects of early life development that ultimately predict a child's long-term health and development.
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ItemShould multiple imputation be stratified by exposure group when estimating causal effects via outcome regression in observational studies?(BMC, 2023-02-16)BACKGROUND: Despite recent advances in causal inference methods, outcome regression remains the most widely used approach for estimating causal effects in epidemiological studies with a single-point exposure and outcome. Missing data are common in these studies, and complete-case analysis (CCA) and multiple imputation (MI) are two frequently used methods for handling them. In randomised controlled trials (RCTs), it has been shown that MI should be conducted separately by treatment group. In observational studies, causal inference is now understood as the task of emulating an RCT, which raises the question of whether MI should be conducted by exposure group in such studies. METHODS: We addressed this question by evaluating the performance of seven methods for handling missing data when estimating causal effects with outcome regression. We conducted an extensive simulation study based on an illustrative case study from the Victorian Adolescent Health Cohort Study, assessing a range of scenarios, including seven outcome generation models with exposure-confounder interactions of differing strength. RESULTS: The simulation results showed that MI by exposure group led to the least bias when the size of the smallest exposure group was relatively large, followed by MI approaches that included the exposure-confounder interactions. CONCLUSIONS: The findings from our simulation study, which was designed based on a real case study, suggest that current practice for the conduct of MI in causal inference may need to shift to stratifying by exposure group where feasible, or otherwise including exposure-confounder interactions in the imputation model.
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ItemHandling of missing data with multiple imputation in observational studies that address causal questions: protocol for a scoping review(BMJ PUBLISHING GROUP, 2023-02)INTRODUCTION: Observational studies in health-related research often aim to answer causal questions. Missing data are common in these studies and often occur in multiple variables, such as the exposure, outcome and/or variables used to control for confounding. The standard classification of missing data as missing completely at random, missing at random (MAR) or missing not at random does not allow for a clear assessment of missingness assumptions when missingness arises in more than one variable. This presents challenges for selecting an analytic approach and determining when a sensitivity analysis under plausible alternative missing data assumptions is required. This is particularly pertinent with multiple imputation (MI), which is often justified by assuming data are MAR. The objective of this scoping review is to examine the use of MI in observational studies that address causal questions, with a focus on if and how (a) missingness assumptions are expressed and assessed, (b) missingness assumptions are used to justify the choice of a complete case analysis and/or MI for handling missing data and (c) sensitivity analyses under alternative plausible assumptions about the missingness mechanism are conducted. METHODS AND ANALYSIS: We will review observational studies that aim to answer causal questions and use MI, published between January 2019 and December 2021 in five top general epidemiology journals. Studies will be identified using a full text search for the term 'multiple imputation' and then assessed for eligibility. Information extracted will include details about the study characteristics, missing data, missingness assumptions and MI implementation. Data will be summarised using descriptive statistics. ETHICS AND DISSEMINATION: Ethics approval is not required for this review because data will be collected only from published studies. The results will be disseminated through a peer reviewed publication and conference presentations. TRIAL REGISTRATION NUMBER: This protocol is registered on figshare (https://doi.org/10.6084/m9.figshare.20010497.v1).
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ItemModelling timing and tempo of adrenarche in a prospective cohort study(PUBLIC LIBRARY SCIENCE, 2022-12-15)To better understand how health risk processes are linked to adrenarche, measures of adrenarcheal timing and tempo are needed. Our objective was to describe and classify adrenal trajectories, in terms of timing and tempo, in a population of children transitioning to adolescence with repeated measurements of salivary dehydroepiandrosterone (DHEA), DHEA-sulphate, and testosterone. We analysed data from the Childhood to Adolescence Transition Study (CATS), a longitudinal study of 1239 participants, recruited at 8-9 years old and followed up annually. Saliva samples were assayed for adrenal hormones. Linear mixed-effect models with subject-specific random intercepts and slopes were used to model longitudinal hormone trajectories by sex and derive measures of adrenarcheal timing and tempo. The median values for all hormones were higher at each consecutive study wave for both sexes, and higher for females than males. For all hormones, between-individual variation in hormone levels at age 9 (timing) was moderately large and similar for females and males. Between-individual variation in hormone progression over time (tempo) was of moderate magnitude compared with the population average age-slope, which itself was small compared with overall hormone level at each age. This suggests that between-individual variation in tempo was less important for modelling hormone trajectories. Between-individual variation in timing was more important for determining relative adrenal hormonal level in childhood than tempo. This finding suggests that adrenal hormonal levels at age 8-9 years can be used to predict relative levels in early adolescence (up to 13 years).