Effects of interpregnancy interval on pregnancy complications: protocol for systematic review and meta-analysis

Introduction: Interpregnancy interval (IPI) is the length of time between a birth and conception of the next pregnancy. Evidence suggests that both short and long IPIs are at increased risk of adverse pregnancy and perinatal outcomes. Relatively less attention has been directed towards investigating the effect of IPI on pregnancy complications, and the studies that have been conducted have shown mixed results. This systematic review will aim to provide an update to the most recent available evidence on the effect of IPI on pregnancy complications. Method and Analysis: We will search electronic databases such as Ovid/MEDLINE, EMBASE, CINAHL, Scopus, Web of Science and PubMed to identify peer-reviewed articles on the effects of IPI on pregnancy complications. We will include articles published from start of indexing until 12 February 2018 without any restriction to geographic setting. We will limit the search to literature published in English language and human subjects. Two independent reviewers will screen titles and abstracts and select full-text articles that meet the eligibility criteria. The Newcastle-Ottawa tool will be used to assess quality of observational studies. Where data permit, meta-analyses will be performed for individual pregnancy complications. A subgroup analyses by country categories (high-income vs low and middle-income countries) based on World Bank income group will be performed. Where meta-analysis is not possible, we will provide a description of data without further attempt to quantitatively pool results. Ethics and Dissemination: Formal ethical approval is not required as primary data will not be collected. The results will be published in peer-reviewed journals and presented at national and international conferences. Prospero Registration Number: CRD42018088578

Implementation of a novel antimicrobial stewardship strategy for rural facilities utilising telehealth

A significant portion of healthcare takes place in small hospitals, and many are located in rural and regional areas. Facilities in these regions frequently do not have adequate resources to implement an onsite antimicrobial stewardship programme and there are limited data relating to their implementation and effectiveness. We present an innovative model of providing a specialist telehealth antimicrobial stewardship service utilising a centralised service (Queensland Statewide Antimicrobial Stewardship Program) to a rural Hospital and Health Service. Results of a 2-year post-implementation follow-up showed an improvement in adherence to guidelines [33.7% (95% CI 27.0–40.4%) vs. 54.1% (95% CI 48.7–59.5%)] and appropriateness of antimicrobial prescribing [49.0% (95% CI 42.2–55.9%) vs. 67.5% (95% CI 62.7–72.4%) (P < 0.001). This finding was sustained after adjustment for hospitals, with improvement occurring sequentially across the years for adherence to guidelines [adjusted odds ratio (aOR) = 2.44, 95% CI 1.70–3.51] and appropriateness of prescribing (aOR = 2.48, 95% CI 1.70–3.61). There was a decrease in mean total antibiotic use (DDDs/1000 patient-days) between the years 2016 (52.82, 95% CI 44.09–61.54) and 2018 (39.74, 95% CI 32.76–46.73), however this did not reach statistical significance. Additionally, there was a decrease in mean hospital length of stay (days) from 2016 (3.74, 95% CI 3.08–4.41) to 2018 (2.55, 95% CI 1.98–3.12), although this was not statistically significant. New telehealth-based models of antimicrobial stewardship can be effective in improving prescribing in rural areas. Programmes similar to ours should be considered for rural facilities

Prevalence of diverse genders and sexualities in Australia and associations with five forms of child maltreatment and multi-type maltreatment

This study presents the most comprehensive national prevalence estimates of diverse gender and sexuality identities in Australians, and the associations with five separate types of child maltreatment and their overlap (multi-type maltreatment). Using Australian Child Maltreatment Study (ACMS) data (N = 8503), 9.5% of participants identified with a diverse sexuality and.9% with a diverse gender. Diverse identities were more prevalent in the youth cohort, with 17.7% of 16–24 years olds identifying with a diverse sexuality and 2.3% with a diverse gender. Gender and sexuality diversity also intersect – for example, with women (aged 16–24 and 25–44) more likely than men to identify as bisexual. The prevalence of physical abuse, sexual abuse, emotional abuse, neglect and exposure to domestic violence was very high for those with diverse sexuality and/or gender identities. Maltreatment was most prevalent for participants in the youth cohort with diverse gender identities (90.5% experiencing some form of child maltreatment; 77% multi-type maltreatment) or diverse sexualities (85.3% reporting any child maltreatment; 64.3% multi-type maltreatment). The strong association found between child maltreatment and diverse sexuality and gender identities is critical for understanding the social and mental health vulnerabilities of these groups, and informing services needed to support them.</p

Stillbirth risk prediction using machine learning for a large cohort of births from Western Australia, 1980–2015

Quantification of stillbirth risk has potential to support clinical decision-making. Studies that have attempted to quantify stillbirth risk have been hampered by small event rates, a limited range of predictors that typically exclude obstetric history, lack of validation, and restriction to a single classifier (logistic regression). Consequently, predictive performance remains low, and risk quantification has not been adopted into antenatal practice. The study population consisted of all births to women in Western Australia from 1980 to 2015, excluding terminations. After all exclusions there were 947,025 livebirths and 5,788 stillbirths. Predictive models for stillbirth were developed using multiple machine learning classifiers: regularised logistic regression, decision trees based on classification and regression trees, random forest, extreme gradient boosting (XGBoost), and a multilayer perceptron neural network. We applied 10-fold cross-validation using independent data not used to develop the models. Predictors included maternal socio-demographic characteristics, chronic medical conditions, obstetric complications and family history in both the current and previous pregnancy. In this cohort, 66% of stillbirths were observed for multiparous women. The best performing classifier (XGBoost) predicted 45% (95% CI: 43%, 46%) of stillbirths for all women and 45% (95% CI: 43%, 47%) of stillbirths after the inclusion of previous pregnancy history. Almost half of stillbirths could be potentially identified antenatally based on a combination of current pregnancy complications, congenital anomalies, maternal characteristics, and medical history. Greatest sensitivity is achieved with addition of current pregnancy complications. Ensemble classifiers offered marginal improvement for prediction compared to logistic regression

Stillbirth risk prediction using machine learning for a large cohort of births from Western Australia, 1980–2015

Quantification of stillbirth risk has potential to support clinical decision-making. Studies that have attempted to quantify stillbirth risk have been hampered by small event rates, a limited range of predictors that typically exclude obstetric history, lack of validation, and restriction to a single classifier (logistic regression). Consequently, predictive performance remains low, and risk quantification has not been adopted into antenatal practice. The study population consisted of all births to women in Western Australia from 1980 to 2015, excluding terminations. After all exclusions there were 947,025 livebirths and 5,788 stillbirths. Predictive models for stillbirth were developed using multiple machine learning classifiers: regularised logistic regression, decision trees based on classification and regression trees, random forest, extreme gradient boosting (XGBoost), and a multilayer perceptron neural network. We applied 10-fold cross-validation using independent data not used to develop the models. Predictors included maternal socio-demographic characteristics, chronic medical conditions, obstetric complications and family history in both the current and previous pregnancy. In this cohort, 66% of stillbirths were observed for multiparous women. The best performing classifier (XGBoost) predicted 45% (95% CI: 43%, 46%) of stillbirths for all women and 45% (95% CI: 43%, 47%) of stillbirths after the inclusion of previous pregnancy history. Almost half of stillbirths could be potentially identified antenatally based on a combination of current pregnancy complications, congenital anomalies, maternal characteristics, and medical history. Greatest sensitivity is achieved with addition of current pregnancy complications. Ensemble classifiers offered marginal improvement for prediction compared to logistic regression

The prevalence of peer sexual harassment during childhood in Australia

Sexual harassment inflicted by adolescents on their peers is a major public health issue, but its prevalence across childhood is not known. We provide the first nationally representative data on the prevalence of peer sexual harassment across childhood, using cross-sectional data from the Australian Child Maltreatment Study (ACMS). The ACMS surveyed 8,503 people aged 16 and over about their experiences of child maltreatment and associated health outcomes. The prevalence of peer sexual harassment was assessed using the Juvenile Victimization Questionnaire (JVQ)-R2 Adapted Version (ACMS), with survey data weighted to reflect characteristics of the Australian population. Overall, 1 in 10 (10.4% (95% Confidence Intervals (CI) [9.7, 11.3])) Australians experienced peer sexual harassment during childhood. Peer sexual harassment is an issue disproportionately affecting gender-diverse individuals (24.0%, 95% CI [15.5, 35.2]) and women (15.3%, 95% CI [14.0, 16.7%]), compared to men (5.0%, 95% CI [4.3, 5.9]). Rates of peer sexual harassment were also very high among sexuality diverse participants (prevalence estimates ranging between 14.2% and 29.8%). Peer sexual harassment was predominately inflicted by male peers (9.6%, 95% CI [8.9, 10.4]), compared to 1.8% (95% CI [1.5, 2.2]) reporting harassment from female peers. These findings have implications for understanding and reducing attitudes supporting peer sexual harassment in childhood, particularly against girls and gender and sexuality diverse youth, and associations with other gendered violence both in childhood and later life

The association between child maltreatment and health risk behaviours and conditions throughout life in the Australian Child Maltreatment Study

Objective To estimate associations between all five types of child maltreatment (emotional abuse, neglect, physical abuse, sexual abuse, and exposure to domestic violence) and health risk behaviours and conditions. Design, setting, participants Nationally representative survey of Australian residents aged 16 years and older conducted by computer-assisted telephone interviewing. Main outcome measures Associations between child maltreatment and the following health risk behaviours and conditions: current smoker, binge drinking (at least weekly in past 12 months), cannabis dependence (according to the Cannabis Severity of Dependence Scale), obesity (based on body mass index), self-harm in past 12 months, and suicide attempt in past 12 months. Results A total of 8503 participants completed the survey. All five types of child maltreatment were associated with increased rates of all of the health risk behaviours and conditions that we considered. The strongest associations were in the youngest age group (16–24-year-olds). Sexual abuse and emotional abuse were associated with the highest odds of health risk behaviours and conditions. Cannabis dependence, self-harm and suicide attempts were most strongly associated with child maltreatment. Experiencing more than one type of child maltreatment was associated with higher rates of health risk behaviours and conditions than experiencing one type of child maltreatment. Conclusions Child maltreatment is associated with substantially increased rates of health risk behaviours and conditions. Prevention and intervention efforts should be informed by trauma histories, and holistic psychosocial care should be incorporated into programs focusing on behaviour change

Child sexual abuse by different classes and types of perpetrator: prevalence and trends from an Australian national survey

Background Little evidence exists about the prevalence of child sexual abuse (CSA) inflicted by different relational classes of perpetrators (e.g., parents; institutional adults; adolescents), and by individual types of perpetrators (e.g., fathers and male relatives; male teachers and male clergy; known and unknown adolescents). Objective To generate evidence of the prevalence of CSA by different perpetrators, and trends by victim gender and age group. Participants and setting The Australian Child Maltreatment Study collected information about CSA victimisation from a nationally-representative sample of 8503 individuals aged 16 and over. Methods We analysed data about 42 perpetrator types, collapsed into eight classes. We generated national prevalence estimates of CSA inflicted by each perpetrator class and individual perpetrator type, and compared results by victim gender and age group. Results Australian CSA prevalence was 28.5%, with the following prevalence by perpetrator classes: other known adolescents (non-romantic): 10.0%; parents/caregivers in the home: 7.8%; other known adults: 7.5%; unknown adults: 4.9%; adolescents (current/former romantic partners): 2.5%; institutional caregivers: 2.0%; siblings: 1.6%; unknown adolescents: 1.4%. Women experienced more CSA by all perpetrator classes except institutional caregivers. Age group comparison showed significant declines in CSA by parents/caregivers, and other known adults; and increases in CSA by adolescents (current/former romantic partners). Individual perpetrator type comparison showed declines in CSA by fathers, male relatives living in the home, non-resident male relatives, and other known male adults; and increases in CSA by known male adolescents, current boyfriends, and former boyfriends. Conclusions CSA by adults has declined, indicating positive impacts of prevention efforts. However, CSA by adolescents has increased. Further declines in CSA by adults are required and possible. Targeted prevention of CSA by adolescents must be prioritised

The prevalence of child maltreatment in Australia: findings from a national survey

Objectives To estimate the prevalence in Australia of each type of child maltreatment; to identify gender- and age group-related differences in prevalence. Design, setting Cross-sectional national survey; mobile telephone interviews using random digit dialling (computer-generated), Australia, 9 April – 11 October 2021. Retrospective self-report data using validated questionnaire (Juvenile Victimisation Questionnaire-R2 Adapted Version (Australian Child Maltreatment Study). Participants People aged 16 years or more. The target sample size was 8500 respondents: 3500 people aged 16–24 years and 1000 respondents each from five further age groups (25–34, 35–44, 45–54, 55–64, 65 years or more). Main outcome measures Proportions of respondents reporting physical abuse, sexual abuse, emotional abuse, neglect, and exposure to domestic violence to age 18 years, assessed with the Juvenile Victimization Questionnaire-R2 Adapted Version (Australian Child Maltreatment Study), overall and by gender and age group, and weighted to reflect characteristics of the Australian population aged 16 years or more in 2016. Results Complete survey data were available for 8503 eligible participants (14% response rate). Physical abuse was reported by 32.0% of respondents (95% confidence interval [CI], 30.7–33.3%), sexual abuse by 28.5% (95% CI, 27.3–29.8%), emotional abuse by 30.9% (95% CI, 29.7–32.2%), neglect by 8.9% (95% CI, 8.1–9.7%), and exposure to domestic violence by 39.6% (95% CI, 38.3–40.9%). The proportions of respondents who reported sexual abuse, emotional abuse, or neglect were each statistically significantly larger for women than men. The reported prevalence of physical abuse by respondents aged 16–24 years was lower than for those aged 25–34 years, and that of sexual abuse was lower than for those aged 35–44 years, suggesting recent declines in the prevalence of these maltreatment types. Conclusions Child maltreatment is common in Australia, and larger proportions of women than men report having experienced sexual abuse, emotional abuse, and neglect during childhood. As physical and sexual abuse may have declined recently, public health policy and practice may have positive effects, justifying continued monitoring and prevention activities

The association between child maltreatment and mental disorders in the Australian Child Maltreatment Study

Objectives To examine the associations between experiences of child maltreatment and mental disorders in the Australian population. Design Population-representative survey conducted by computer-assisted telephone interviewing. Setting, participants Australian residents aged 16 years and older. Main outcome measures Mental disorder diagnoses of lifetime major depressive disorder, current alcohol use disorder (mild, moderate and severe), current generalised anxiety disorder and current post-traumatic stress disorder. Results More than one in three Australians (3606/8503 surveyed participants; 38.0%; 95% CI, 36.7–39.3%) met the diagnostic criteria for a mental disorder. The prevalence of mental disorders in non-maltreated participants was 21.6% (95% CI, 19.9–23.3%; n = 851). This increased to 36.2% (95% CI, 33.5–38.9%; n = 764) for those who experienced a single type of maltreatment and 54.8% (95% CI, 52.6–56.9%; n = 1991) for participants who experienced multi-type maltreatment. Compared with non-maltreated Australians, maltreated participants had about three times the odds of any mental disorder (odds ratio [OR], 2.82; 95% CI, 2.47–3.22), generalised anxiety disorder (OR, 3.14; 95% CI, 2.48–3.97), major depressive disorder (OR, 3.19; 95% CI, 2.68–3.80) and severe alcohol use disorder (OR, 2.62; 95% CI, 1.83–3.76), and almost five times the odds of post-traumatic stress disorder (OR, 4.60; 95% CI, 3.00–7.07). Associations between experiences of child maltreatment and mental disorders were strongest for sexual abuse, emotional abuse and multi-type maltreatment. The strength of the associations did not differ by gender. Adjustment for childhood and current financial hardship and for current socio-economic status did not significantly attenuate the associations. Conclusions Mental disorders are significantly more likely to occur in individuals who experience child maltreatment, particularly multi-type maltreatment. Prevention of child maltreatment provides an opportunity to substantially reduce the prevalence of mental illness and improve the health of the Australian population