Going public : do risk and choice explain differences in caesarean birth rates between public and private places of birth in Australia?

Background: Women who birth in private facilities in Australia are more likely to have a caesarean birth than women who birth in public facilities and these differences remain after accounting for sector differences in the demographic and health risk profiles of women. However, the extent to which women’s preferences and/or freedom to choose their mode of birth further account for differences in the likelihood of caesarean birth between the sectors remains untested. Method: Women who birthed in Queensland, Australia during a two-week period in 2009 were mailed a self-report survey approximately three months after birth. Seven hundred and fifty-seven women provided cross-sectional retrospective data on where they birthed (public or private facility), mode of birth (vaginal or caesarean) and risk factors, along with their preferences and freedom to choose their mode of birth. A hierarchical logistic regression was conducted to determine the extent to which maternal risk and freedom to choose one’s mode of birth explain sector differences in the likelihood of having a caesarean birth. Findings: While there was no sector difference in women’s preference for mode of birth, women who birthed in private facilities had higher odds of feeling able to choose either a vaginal or caesarean birth, and feeling able to choose only a caesarean birth. Women had higher odds of having caesarean birth if they birthed in private facilities, even after accounting for significant risk factors such as age, body mass index, previous caesarean and use of assisted reproductive technology. However, there was no association between place of birth and odds of having a caesarean birth after also accounting for freedom to choose one’s mode of birth. Conclusions: These findings call into question suggestions that the higher caesarean birth rate in the private sector in Australia is attributable to increased levels of obstetric risk among women birthing in the private sector or maternal preferences alone. Instead, the determinants of sector differences in the likelihood of caesarean births are complex and are linked to differences in the perceived choices for mode of birth between women birthing in the private and public systems.

Distinguishing between mean-field, moment dynamics and stochastic descriptions of birth-death-movement processes

Mathematical descriptions of birth–death–movement processes are often calibrated to measurements from cell biology experiments to quantify tissue growth rates. Here we describe and analyze a discrete model of a birth–death-movement process applied to a typical two–dimensional cell biology experiment. We present three different descriptions of the system: (i) a standard mean–field description which neglects correlation effects and clustering; (ii) a moment dynamics description which approximately incorporates correlation and clustering effects, and; (iii) averaged data from repeated discrete simulations which directly incorporates correlation and clustering effects. Comparing these three descriptions indicates that the mean–field and moment dynamics approaches are valid only for certain parameter regimes, and that both these descriptions fail to make accurate predictions of the system for sufficiently fast birth and death rates where the effects of spatial correlations and clustering are sufficiently strong. Without any method to distinguish between the parameter regimes where these three descriptions are valid, it is possible that either the mean–field or moment dynamics model could be calibrated to experimental data under inappropriate conditions, leading to errors in parameter estimation. In this work we demonstrate that a simple measurement of agent clustering and correlation, based on coordination number data, provides an indirect measure of agent correlation and clustering effects, and can therefore be used to make a distinction between the validity of the different descriptions of the birth–death–movement process.

Season of birth and location of residence: Defining the role of ultraviolet radiation exposure on childhood temperament and behaviour

This thesis added new insight to research knowledge about the role that season and ultraviolet radiation (UV) exposure during pregnancy has on children's temperament and behaviours, using a nation-wide longitudinal study. It was found that young children born in summer months are likely to have problematic behaviours. The thesis also found that summer-born children are likely to receive lowest levels of UV exposure during the gestational period. Finally, this work showed that low gestational UV exposure is associated with an increased risk of behavioural problems in children.

The impact of nonlinear exposure risk relationships on seasonal time series data: modelling danish neonatal birth anthropometric data

Background Birth weight and length have seasonal fluctuations. Previous analyses of birth weight by latitude effects identified seemingly contradictory results, showing both 6 and 12 monthly periodicities in weight. The aims of this paper are twofold: (a) to explore seasonal patterns in a large, Danish Medical Birth Register, and (b) to explore models based on seasonal exposures and a non-linear exposure-risk relationship. Methods Birth weight and birth lengths on over 1.5 million Danish singleton, live births were examined for seasonality. We modelled seasonal patterns based on linear, U- and J-shaped exposure-risk relationships. We then added an extra layer of complexity by modelling weighted population-based exposure patterns. Results The Danish data showed clear seasonal fluctuations for both birth weight and birth length. A bimodal model best fits the data, however the amplitude of the 6 and 12 month peaks changed over time. In the modelling exercises, U- and J-shaped exposure-risk relationships generate time series with both 6 and 12 month periodicities. Changing the weightings of the population exposure risks result in unexpected properties. A J-shaped exposure-risk relationship with a diminishing population exposure over time fitted the observed seasonal pattern in the Danish birth weight data. Conclusion In keeping with many other studies, Danish birth anthropometric data show complex and shifting seasonal patterns. We speculate that annual periodicities with non-linear exposure-risk models may underlie these findings. Understanding the nature of seasonal fluctuations can help generate candidate exposures.

Young women's recent experience of labour and birth care in Queensland

Background Young parenthood continues to be an issue of concern in terms of clinical and psychosocial outcomes for mothers and their babies, with higher rates of medical complications such as preterm labour and hypertensive disease and a higher risk of depression. The aim of this study was to investigate how young age impacts on women's experience of intrapartum care. Methods Secondary analysis of data collected in a population based survey of women who had recently given birth in Queensland, comparing clinical and interpersonal aspects of the intrapartum maternity care experience for 237 eligible women aged 15–20 years and 6534 aged more than 20 years. Descriptive and multivariate analyses were undertaken. Results In the univariate analysis a number of variables were significantly associated with clinical aspects of labour and birth and perceptions of care: young women were more likely to birth in a public facility, to travel for birth and to live in less economically advantaged areas, to have a normal vaginal birth and to have one carer through labour. They were also less likely to report being treated with respect and kindness and talked to in a way they could understand. In logistic regression models, after adjustment for parity, other socio-demographic factors and mode of birth, younger mothers were still more likely to birth in a public facility, to travel for birth, to be more critical about interpersonal and aspects of care and the hospital or birth centre environment. Conclusion This study shows how experience of care during labour and birth is different for young women. Young women reported poorer quality interpersonal care which may well reflect an inferior care experience and stereotyping by health professionals, indicating a need for more effective staff engagement with young women at this time.

Environments For Healthy Living (EFHL) Griffith birth cohort study : characteristics of sample and profile of antenatal exposures

Background The Environments for Healthy Living (EFHL) study is a repeated sample, longitudinal birth cohort in South East Queensland, Australia. We describe the sample characteristics and profile of maternal, household, and antenatal exposures. Variation and data stability over recruitment years were examined. Methods Four months each year from 2006, pregnant women were recruited to EFHL at routine antenatal visits on or after 24 weeks gestation, from three public maternity hospitals. Participating mothers completed a baseline questionnaire on individual, familial, social and community exposure factors. Perinatal data were extracted from hospital birth records. Descriptive statistics and measures of association were calculated comparing the EFHL birth sample with regional and national reference populations. Data stability of antenatal exposure factors was assessed across five recruitment years (2006–2010 inclusive) using the Gamma statistic for ordinal data and chi-squared for nominal data. Results Across five recruitment years 2,879 pregnant women were recruited which resulted in 2904 live births with 29 sets of twins. EFHL has a lower representation of early gestational babies, fewer still births and a lower percentage of low birth weight babies, when compared to regional data. The majority of women (65%) took a multivitamin supplement during pregnancy, 47% consumed alcohol, and 26% reported having smoked cigarettes. There were no differences in rates of a range of antenatal exposures across five years of recruitment, with the exception of increasing maternal pre-pregnancy weight (p=0.0349), decreasing rates of high maternal distress (p=0.0191) and decreasing alcohol consumption (p<0.0001). Conclusions The study sample is broadly representative of births in the region and almost all factors showed data stability over time. This study, with repeated sampling of birth cohorts over multiple years, has the potential to make important contributions to population health through evaluating longitudinal follow-up and within cohort temporal effects.

Determinants of pre-hospital care non-usage for patients with emergency care needs [including commentary by Snooks H.]

Objective-To establish the demographic, health status and insurance determinants of pre-hospital ambulance non-usage for patients with emergency medical needs. Methods-Triage category, date of birth, sex, marital status, country of origin, method and time of arrival, ambulance insurance status, diagnosis, and disposal were collected for all patients who presented over a four month period (n=10 229) to the emergency department of a major provincial hospital. Data for patients with urgent (n=678) or critical care needs (n=332) who did not use pre-hospital care were analysed using Poisson regression. Results-Only a small percentage (6.6%) of the total sample were triaged as having urgent medical needs or critical care needs (3.2%). Predictors of usage for those with urgent care needs included age greater than 65 years (prevalence ratio (PR)=0.54; 95% confidence interval (CI)= 0.35 to 0.83), being admitted to intensive care or transferred to another hospital (PR=0.62; 95% CI=0.44 to 0.89) or ward (PR=0.72; 95% CI=0.56 to 0.93) and ambulance insurance status (PR=0.67; 95% CI=052 to 0.86). Sex, marital status, time of day and country of origin were not predictive of usage and non-usage. Predictors of usage for those with critical care needs included age 65 years or greater (PR=0.45; 95% CI=0.25 to 0.81) and a diagnosis of trauma (PR=0.49; 95% CI=0.26 to 0.92). A non-English speaking background was predictive of non-usage (PR=1.98; 95% CI=1.06 to 3.70). Sex, marital status, time of day, triage and ambulance insurance status were not predictive of non-usage. Conclusions-Socioeconomic and medical factors variously influence ambulance usage depending on the severity or urgency of the medical condition. Ambulance insurance status was less of an influence as severity of condition increased suggesting that, at a critical level of urgency, patients without insurance are willing to pay for a pre-hospital ambulance service.

Inequalities in cardiovascular disease mortality : the role of behavioural, physiological and social risk factors

Background: While the relationship between socioeconomic disadvantage and cardiovascular disease (CVD) is well established, the role that traditional cardiovascular risk factors play in this association remains unclear. We examined the association between education attainment and CVD mortality and the extent to which behavioural, social and physiological factors explained this relationship. Methods: Adults (n=38 355) aged 40-69 years living in Melbourne, Australia were recruited in 1990-1994. Subjects with baseline CVD risk factor data ascertained through questionnaire and physical measurement were followed for an average of 9.4 years with CVD deaths verified by review of medical records and autopsy reports. Results: CVD mortality was higher for those with primary education only compared to those who had completed tertiary education, with a hazard ratio (HR) of 1.66 (95% confidence interval [CI] 1.11-2.49) after adjustment for age, country of birth and gender. Those from the lowest educated group had a more adverse cardiovascular risk factor profile compared to the highest educated group, and adjustment for these risk factors reduced the HR to 1.18 (95% CI 0.78-1.77). In analysis of individual risk factors, smoking and waist circumference explained most of the difference in CVD mortality between the highest and lowest education groups. Conclusions: Most of the excess CVD mortality in lower socioeconomic groups can be explained by known risk factors, particularly smoking and overweight. While targeting cardiovascular risk factors should not divert efforts from addressing the underlying determinants of health inequalities, it is essential that known risk factors are addressed effectively among lower socioeconomic groups.

Addressing issues in sparseness, ecological bias and formulation of the adjacency matrix in Bayesian spatio-temporal analysis of disease counts

The main objective of this PhD was to further develop Bayesian spatio-temporal models (specifically the Conditional Autoregressive (CAR) class of models), for the analysis of sparse disease outcomes such as birth defects. The motivation for the thesis arose from problems encountered when analyzing a large birth defect registry in New South Wales. The specific components and related research objectives of the thesis were developed from gaps in the literature on current formulations of the CAR model, and health service planning requirements. Data from a large probabilistically-linked database from 1990 to 2004, consisting of fields from two separate registries: the Birth Defect Registry (BDR) and Midwives Data Collection (MDC) were used in the analyses in this thesis. The main objective was split into smaller goals. The first goal was to determine how the specification of the neighbourhood weight matrix will affect the smoothing properties of the CAR model, and this is the focus of chapter 6. Secondly, I hoped to evaluate the usefulness of incorporating a zero-inflated Poisson (ZIP) component as well as a shared-component model in terms of modeling a sparse outcome, and this is carried out in chapter 7. The third goal was to identify optimal sampling and sample size schemes designed to select individual level data for a hybrid ecological spatial model, and this is done in chapter 8. Finally, I wanted to put together the earlier improvements to the CAR model, and along with demographic projections, provide forecasts for birth defects at the SLA level. Chapter 9 describes how this is done. For the first objective, I examined a series of neighbourhood weight matrices, and showed how smoothing the relative risk estimates according to similarity by an important covariate (i.e. maternal age) helped improve the model’s ability to recover the underlying risk, as compared to the traditional adjacency (specifically the Queen) method of applying weights. Next, to address the sparseness and excess zeros commonly encountered in the analysis of rare outcomes such as birth defects, I compared a few models, including an extension of the usual Poisson model to encompass excess zeros in the data. This was achieved via a mixture model, which also encompassed the shared component model to improve on the estimation of sparse counts through borrowing strength across a shared component (e.g. latent risk factor/s) with the referent outcome (caesarean section was used in this example). Using the Deviance Information Criteria (DIC), I showed how the proposed model performed better than the usual models, but only when both outcomes shared a strong spatial correlation. The next objective involved identifying the optimal sampling and sample size strategy for incorporating individual-level data with areal covariates in a hybrid study design. I performed extensive simulation studies, evaluating thirteen different sampling schemes along with variations in sample size. This was done in the context of an ecological regression model that incorporated spatial correlation in the outcomes, as well as accommodating both individual and areal measures of covariates. Using the Average Mean Squared Error (AMSE), I showed how a simple random sample of 20% of the SLAs, followed by selecting all cases in the SLAs chosen, along with an equal number of controls, provided the lowest AMSE. The final objective involved combining the improved spatio-temporal CAR model with population (i.e. women) forecasts, to provide 30-year annual estimates of birth defects at the Statistical Local Area (SLA) level in New South Wales, Australia. The projections were illustrated using sixteen different SLAs, representing the various areal measures of socio-economic status and remoteness. A sensitivity analysis of the assumptions used in the projection was also undertaken. By the end of the thesis, I will show how challenges in the spatial analysis of rare diseases such as birth defects can be addressed, by specifically formulating the neighbourhood weight matrix to smooth according to a key covariate (i.e. maternal age), incorporating a ZIP component to model excess zeros in outcomes and borrowing strength from a referent outcome (i.e. caesarean counts). An efficient strategy to sample individual-level data and sample size considerations for rare disease will also be presented. Finally, projections in birth defect categories at the SLA level will be made.

Editoral : Correspondence regarding Anker SD, Koehler F, Abraham WT. Telemedicine and remote management of patients with heart failure. The Lancet 2011; 378: 731–39. Published 20 August 2011.

We read the excellent review of telemonitoring in chronic heart failure (CHF)1 with interest and commend the authors on the proposed classification of telemedical remote management systems according to the type of data transfer, decision ability and level of integration. However, several points require clarification in relation to our Cochrane review of telemonitoring and structured telephone support2. We included a study by Kielblock3. We corresponded directly with this study team specifically to find out whether or not this was a randomised study and were informed that it was a randomised trial, albeit by date of birth. We note in our review2 that this randomisation method carries a high risk of bias. Post-hoc metaanalyses without these data demonstrate no substantial change to the effect estimates for all cause mortality (original risk ratio (RR) 0·66 [95% CI 0·54, 0·81], p<0·0001; revised RR 0·72 [95% CI 0·57, 0·92], p=0·008), all-cause hospitalisation (original RR 0·91 [95% CI 0·84, 0·99] p=0·02; revised RR 0.92 [95% CI 0·84, 1·02], p=0·10 ) or CHF-related hospitalisation (original RR 0·79 [95% CI 0·67, 0·94] p=0·008; revised RR 0·75 [95% CI 0·60, 0·94] p=0·01). Secondly, we would classify the Tele-HF study4, 5 as structured telephone support, rather than telemonitoring. Again, inclusion of these data alters the point-estimate but not the overall result of the meta-analyses4. Finally, our review2 does not include invasive telemonitoring as the search strategy was not designed to capture these studies. Therefore direct comparison of our review findings with recent studies of these interventions is not recommended.

An ingenious decision support system for remote health monitoring of pregnant women

Maternal deaths have been a critical issue for women living in rural and remote areas. The need to travel long distances, the shortage of primary care providers such as physicians, specialists and nurses, and the closing of small hospitals have been problems identified in many rural areas. Some research work has been undertaken and a few techniques have been developed to remotely measure the physiological condition of pregnant women through sophisticated ultrasound equipment. There are numerous ways to reduce maternal deaths, and an important step is to select the right approaches to achieving this reduction. One such approach is the provision of decision support systems in rural and remote areas. Decision support systems (DSSs) have already shown a great potential in many health fields. This thesis proposes an ingenious decision support system (iDSS) based on the methodology of survey instruments and identification of significant variables to be used in iDSS using statistical analysis. A survey was undertaken with pregnant women and factorial experimental design was chosen to acquire sample size. Variables with good reliability in any one of the statistical techniques such as Chi-square, Cronbach’s á and Classification Tree were incorporated in the iDSS. The decision support system was developed with significant variables such as: Place of residence, Seeing the same doctor, Education, Tetanus injection, Baby weight, Previous baby born, Place of birth, Assisted delivery, Pregnancy parity, Doctor visits and Occupation. The ingenious decision support system was implemented with Visual Basic as front end and Microsoft SQL server management as backend. Outcomes of the ingenious decision support system include advice on Symptoms, Diet and Exercise to pregnant women. On conditional system was sent and validated by the gynaecologist. Another outcome of ingenious decision support system was to provide better pregnancy health awareness and reduce long distance travel, especially for women in rural areas. The proposed system has qualities such as usefulness, accuracy and accessibility.

Birth outcomes after spontaneous or assisted conception among infertile Australian women aged 28 to 36 years: A prospective, population-based study

Objective To examine the extent to which the odds of birth, pregnancy, or adverse birth outcomes are higher among women aged 28 to 36 years who use fertility treatment compared with untreated women. Design Prospective, population-based. Setting Not applicable. Patient(s) Participants in the ALSWH born in 1973 to 1978 who reported on their infertility and use of in vitro fertilization (IVF) or ovulation induction (OI). Intervention(s) Postal survey questionnaires administered as part of ALSWH. Main Outcome Measure(s) Among women treated with IVF or OI and untreated women, the odds of birth outcomes estimated by use of adjusted logistic regression modeling. Result(s) Among 7,280 women, 18.6% (n = 1,376) reported infertility. Half (53.0%) of the treated women gave birth compared with 43.8% of untreated women. Women with prior parity were less likely to use IVF compared with nulliparous women. Women using IVF or OI, respectively, were more likely to have given birth after treatment or be pregnant compared with untreated women. Women using IVF or OI were as likely to have ectopic pregnancies, stillbirths, or premature or low birthweight babies as untreated women. Conclusion(s) More than 40% of women aged 28–36 years reporting a history of infertility can achieve births without using treatment, indicating they are subfertile rather than infertile.

Lost and found : improving ascertainment of refugee-background Australians in population datasets

Humanitarian entrants remain invisible in existing populations datasets, and this has significant implications for health care and health policy. We suggest adding 'year of arrival' to population datasets; enabling the combination of 'country of birth' and 'year of arrival' to be used as a proxy for refugee status.