BACKGROUND:This study aimed to investigate the (1) survival probabilities of prefabricated zirconia crowns (PZCs) placed on primary teeth and (2) identify demographic and tooth-related factors that might affect survival probability. METHODS:This study prospectively followed children treated under general anaesthesia by a single practitioner between 2012 and 2020. Demographic variables including the age at treatment, gender and tooth-related variables including FDI tooth number, crown size used and any procedural complications at postoperative reviews were collected. RESULTS:A total of 155 children involving 319 teeth with PZCs were followed up between 12 and 78 months postoperatively with a mean of 38 months. Of the 319 crowns followed, five failures were observed in three patients requiring extraction. Other procedural complications noted included fracture (n = 3), overhangs (n = 3), internal resorption (n = 5) and 24% of crowns showed signs of radiographic changes on postoperative radiographs when these were taken. Age at treatment, tooth type and need for pulp therapy were not statistically associated with clinical success (P > 0.1). CONCLUSIONS:PZCs provide an aesthetic and durable solution in the management of children with early childhood caries. This study shows very good clinical success and survival extending up to 78 months for PZCs placed on primary teeth under general anaesthesia.

While the analysis of gait and balance can be an important indicator of age- or disease-related changes, it remains unclear if repeated performance of gait and balance tests in healthy adults leads to habituation effects, if short-term gait and balance training can improve gait and balance performance, and whether the placement of wearable sensors influences the measurement accuracy. Healthy adults were assessed before and after performing weekly gait and balance tests over three weeks by using a force plate, motion capturing system and smartphone. The intervention group (n = 25) additionally received a home-based gait and balance training plan. Another sample of healthy adults (n = 32) was assessed once to analyze the impact of sensor placement (lower back vs. lower abdomen) on gait and balance analysis. Both the control and intervention group exhibited improvements in gait/stance. However, the trends over time were similar for both groups, suggesting that targeted training and repeated task performance equally contributed to the improvement of the measured variables. Since no significant differences were found in sensor placement, we suggest that a smartphone used as a wearable sensor could be worn both on the lower abdomen and the lower back in gait and balance analyses.

Precise population counts facilitate reliable estimation of differences in disease risk between population sub-groups or geographic regions, which informs rational public health decision-making. In Australia, Census population counts obtainable via the Australian Bureau of Statistics' (ABS') TableBuilder tool, which are widely used, are routinely perturbed to protect privacy. We examine this perturbation's impact on: the precision of TableBuilder population counts, and a geospatial analysis of high-risk foot (HRF) hospital admissions among Western Australian (WA) Indigenous people. The former is severely compromised, disproportionately so for Indigenous people and under the currently employed 'perturbation without additivity' (PWoA) approach. E.g., based on fine-resolution, PWoA-affected data, the Indigenous population total for 'Inner City' WA was >50% lower than its true total. Imprecise calculation of WA Indigenous HRF admission counts, and misrepresentation of high-rate regions of such admissions in Perth, resulted. An approach suggested to manage this - examination of coarse-resolution data - is inadequate, partly due the modifiable areal unit problem. However, a novel map overlay technique alleviates this issue. We recommend that the ABS review the PWoA approach and consider implementing different statistical disclosure control techniques or reverting to the previously employed 'perturbation with additivity' approach, prior to releasing data from the 2021 Australian Census.

OBJECTIVES:It is well known that there are associations between overall health, age, socioeconomic status and rural residency. The objective of this study was to determine the distribution of Australia's aged population by socioeconomic status, as well as remoteness.METHODS:The study employed the Australian Statistical Geography Standard (Statistical Area Level 1 and Remoteness Areas). The database of the geographic boundaries was integrated into the ageing population and socioeconomic data using the Geographic Information System. The socioeconomic data was analysed through the Index of Relative Socioeconomic Disadvantage.RESULTS:Over a decade, the older population in Australia has increased noticeably. In 2016, there was a high percentage of older people (≥65 years) in Tasmania (Tas), 19%, while the lowest percentage was recorded in the Northern Territory (NT), 7%. Across the country, Tasmania had the highest percentage of older citizens living in the most disadvantaged areas since 2006, with 48% recorded in 2016. There was an association between the remoteness areas and the education and income levels of the ageing cohort. However, this association differed between the states and territories. This socioeconomic gap becomes more evident in the very remote areas of the country.CONCLUSIONS:The ageing population in Australia is increasing rapidly; this was associated with an evolving socioeconomic disparity among this ageing society. Our results demonstrated that socioeconomic inequalities were to be found among the older people based on their distribution over the remoteness areas in Australia. This information should be used to target healthcare and ageing policies that meet the specific needs of older people.

Appropriate prioritisation of geographic target regions (TRs) for healthcare interventions is critical to ensure the efficient distribution of finite healthcare resources. In delineating TRs, both 'targeting efficiency', i.e., the return on intervention investment, and logistical factors, e.g., the number of TRs, are important. However, existing approaches to delineate TRs disproportionately prioritise targeting efficiency. To address this, we explored the utility of a method found within conservation planning: the software Marxan and an extension, MinPatch ('Marxan + MinPatch'), with comparison to a new method we introduce: the Spatial Targeting Algorithm (STA). Using both simulated and real-world data, we demonstrate superior performance of the STA over Marxan + MinPatch, both with respect to targeting efficiency and with respect to adequate consideration of logistical factors. For example, by design, and unlike Marxan + MinPatch, the STA allows for user-specification of a desired number of TRs. More broadly, we find that, while Marxan + MinPatch does consider logistical factors, it also suffers from several limitations, including, but not limited to, the requirement to apply two separate software tools, which is burdensome. Given these results, we suggest that the STA could reasonably be applied to help prevent inefficiencies arising due to targeting of interventions using currently available approaches.

Temporal development of maternal and infant microbiomes during early life impacts short- and long-term infant health. This study aimed to characterize bacterial dynamics within maternal faecal, human milk (HM), infant oral, and infant faecal samples during the exclusive breastfeeding period and to document associations between human milk oligosaccharide (HMO) intakes and infant oral and faecal bacterial profiles. Maternal and infant samples (n = 10) were collected at 2–5, 30, 60, 90 and 120 days postpartum and the full-length 16S ribosomal RNA (rRNA) gene was sequenced. Nineteen HMOs were quantitated using high-performance liquid chromatography. Bacterial profiles were unique to each sample type and changed significantly over time, with a large degree of intra- and inter-individual variation in all sample types. Beta diversity was stable over time within infant faecal, maternal faecal and HM samples, however, the infant oral microbiota at day 2–5 significantly differed from all other time points (all p < 0.02). HMO concentrations and intakes significantly differed over time, and HMO intakes showed differential associations with taxa observed in infant oral and faecal samples. The direct clinical relevance of this, however, is unknown. Regardless, future studies should account for intakes of HMOs when modelling the impact of HM on infant growth, as it may have implications for infant microbiota development.

Misallocation of finite healthcare resources can occur when guided by maps that are produced using aggregate-level administrative units. Such maps are affected by the modifiable areal unit problem (MAUP), which describes how patterns may change depending on the particular choice of mapping unit. Smoothing can help avoid this unintended yet detrimental phenomenon. This paper compares the utility of aggregate-level administrative units and smoothing for exploring variation in lower urgency emergency department (ED) presentations across metropolitan Perth, Western Australia. Rates of such presentations were mapped using Australian Bureau of Statistics Statistical Areas Levels 1, 2, and 3 (SA1-3s) and the recently proposed Overlay Aggregation Method (OAM). Resulting maps were compared based on their ability to represent local variation in rates and optimise the targeting and logistical efficiency of geographically targeted resource allocation. SA1-level variation in rates was increasingly obscured by SA2s and SA3s. OAM helped avoid this pitfall, facilitating stable identification of SA1-resolution, high-rate regions while preserving privacy, mitigating the MAUP, and balancing the targeting and logistical efficiency of planned resource allocation to those regions. Routine application of smoothing can help avoid issues undermining maps of lower urgency ED presentations and other health outcomes that are based on aggregate-level administrative units.

The burden of oral health care increases among older people, with a profound challenge in utilising dental services in primary dental care settings. This study aimed to analyse two decades of nationwide hospital separation patterns due to oral health-related conditions among older people. Ageing population data were obtained from the Australian Bureau of Statistics, including people aged 65 years and older. All principal diagnoses of oral health conditions (ICD-10-AM) were analysed in this study. The hospitalisation data included all separations of older people for the financial years 1998–1999 to 2018–2019. A total of 205,461 hospital separations were recorded for older people over a period of twenty-one years. More than 60% of these separations were collectively attributed to dental caries, disorders of teeth and supporting structures, diseases of the jaws, diseases of the pulp and periapical tissues. However, the average rate of separations per 10,000 people due to dental caries was the highest among the dental conditions (8.68). Furthermore, the remaining oral health-related conditions predict an annual percentage increase in the rate that would compromise their oral health quality of life. Dental caries and its sequela seem to be the leading cause for oral health-related hospital admissions in Australia for people aged 65 and older. This could be an indicator of the inadequacy of disease management in the primary dental care setting.

Human milk is a complex and variable ecosystem fundamental to the development of newborns. This study aimed to investigate relationships between human milk oligosaccharides (HMO) and human milk bacterial profiles and infant body composition. Human milk samples (n = 60) were collected at two months postpartum. Infant and maternal body composition was measured with bioimpedance spectroscopy. Human milk bacterial profiles were assessed using full-length 16S rRNA gene sequencing and 19 HMOs were quantitated using high-performance liquid chromatography. Relative abundance of human milk bacterial taxa were significantly associated with concentrations of several fucosylated and sialylated HMOs. Individual human milk bacteria and HMO intakes and concentrations were also significantly associated with infant anthropometry, fat-free mass, and adiposity. Furthermore, when data were stratified based on maternal secretor status, some of these relationships differed significantly among infants born to secretor vs non-secretor mothers. In conclusion, in this pilot study the human milk bacterial profile and HMO intakes and concentrations were significantly associated with infant body composition, with associations modified by secretor status. Future research designed to increase the understanding of the mechanisms by which HMO and human milk bacteria modulate infant body composition should include intakes in addition to concentrations.

Drought is thought to impact upon the mental health of agricultural communities, but studies of this relationship have reported inconsistent results. A source of inconsistency could be the aggregation of data by a single spatiotemporal unit of analysis, which induces the modifiable areal and temporal unit problems. To investigate this, mental health-related emergency department (MHED) presentations among residents of the Wheat Belt region of Western Australia, between 2002 and 2017, were examined. Average daily rainfall was used as a measure of drought. Associations between MHED presentations and rainfall were estimated based on various spatial aggregations of underlying data, at multiple temporal windows. Wide variation amongst results was observed. Despite this, two key features were found: Associations between MHED presentations and rainfall were generally positive when rainfall was measured in summer months (rate ratios up to 1.05 per 0.5 mm of daily rainfall) and generally negative when rainfall was measured in winter months (rate ratios as low as 0.96 per 0.5 mm of daily rainfall). These results demonstrate that the association between drought and mental health is quantifiable; however, the effect size is small and varies depending on the spatial and temporal arrangement of the underlying data. To improve understanding of this association, more studies should be undertaken with longer time spans and examining specific mental health outcomes, using a wide variety of spatiotemporal units.

Long-term future prediction of geographic areas with high rates of potentially preventable hospitalisations (PPHs) among residents, or "hotspots", is critical to ensure the effective location of place-based health service interventions. This is because such interventions are typically expensive and take time to develop, implement, and take effect, and hotspots often regress to the mean. Using spatially aggregated, longitudinal administrative health data, we introduce a method to make such predictions. The proposed method combines all subset model selection with a novel formulation of repeated k-fold cross-validation in developing optimal models. We illustrate its application predicting three-year future hotspots for four PPHs in an Australian context: type II diabetes mellitus, heart failure, chronic obstructive pulmonary disease, and "high risk foot". In these examples, optimal models are selected through maximising positive predictive value while maintaining sensitivity above a user-specified minimum threshold. We compare the model's performance to that of two alternative methods commonly used in practice, i.e., prediction of future hotspots based on either: (i) current hotspots, or (ii) past persistent hotspots. In doing so, we demonstrate favourable performance of our method, including with respect to its ability to flexibly optimise various different metrics. Accordingly, we suggest that our method might effectively be used to assist health planners predict excess future demand of health services and prioritise placement of interventions. Furthermore, it could be used to predict future hotspots of non-health events, e.g., in criminology.

Objective To examine the impact of the modifiable areal unit problem (MAUP) in an investigation of factors associated with ED demand in Perth, Western Australia, in 2016. Furthermore, to advocate a means of avoiding this impact. Methods ED presentations were classified as: urgent medical, non-urgent medical, urgent trauma or non-urgent trauma. In each group, sex-stratified, age-adjusted multivariate associations with socio-economic status and distance to the nearest ED and general practitioner (GP) were estimated. Modelling was undertaken using different sets of spatial units: Australian Bureau of Statistics (ABS) Statistical Areas Level 1 (SA1s) and numerous aggregate-level zonations of SA1s (ABS SA2s and others). Results Estimates obtained using the different units often varied widely: for seven (30%) of 24 strata defined by combinations of sex, ED type and covariate, the smallest and largest effect sizes differed in terms of direction; further, for 11 (65%) of the remaining 17 strata, the largest effect size was at least twice as high as the smallest. This demonstrates the MAUP's impact and that analyses based on a single set of spatial units are unreliable. To resolve the observed variation, we highlight the SA1-level estimates. Conclusions When formulating interventions targeting reduced ED utilisation, policy planners should be guided by evidence based on analysis of appropriate spatial units. This ideal is undermined by the widespread lack of acknowledgement of the MAUP in studies examining drivers of ED demand using spatially aggregated data. To avoid the MAUP, only estimates obtained through examining a minimal geographic unit should be relied upon.

OBJECTIVES:To identify changes in orthodontic management strategies in patients with hypodontia seen in 2000, 2010, and 2017/2018 (during a 1-year period).MATERIALS AND METHODS:An assessment of the panoramic radiographs of 3701 patients from a Western Australian private practice identified 276 individuals demonstrating hypodontia. The location of missing teeth, age, sex, type of malocclusion, and the management strategies (space closure or opening) for each patient were noted.RESULTS:Most hypodontia involved agenesis of three or fewer teeth (90%). Maxillary lateral incisors and mandibular second premolars were the most commonly missing teeth. Female preponderance was noted. When considering treatment, the odds ratio for orthodontic space opening and prosthetic replacement in 2000 was 3.266 (P value = 7e-04; 95% confidence interval [CI], 1.464-4.633) compared with patients seen in 2010 and 1.632 (P value = 7e-04; 95% CI, 0.811-2.434) compared with patients in 2017/2018. For patients demonstrating bilateral absence of maxillary lateral incisors, the odds ratio for orthodontic space opening was 3.185 (P value = 0.0215; 95% CI, 1.182-9.243) compared with counterparts with unilateral agenesis. None of the factors investigated were significantly associated with the types of treatment planned/provided for the patients with missing mandibular second premolars.CONCLUSIONS:Maxillary lateral incisors and mandibular second premolars were the most commonly missing teeth. A trend away from space opening and prosthetic replacement toward orthodontic space closure was observed from 2000 to 2017/2018. This may reflect a change in attitude toward prosthetic replacement options and/or greater optimism with biomechanical strategies since the implementation of temporary anchorage devices to assist in space closure.

Background: Residual neuromuscular block is associated with an increased risk of postoperative pulmonary complications in retrospective studies. The aim of our study was to investigate prospectively the incidence of postoperative pulmonary complications after reversal with either sugammadex (SUG) or neostigmine (NEO) in high-risk older patients. Methods: We randomly allocated 180 older patients with significant morbidity (ASA physical status 3) >= 75 yr old to reversal of rocuronium with either SUG or NEO. Adverse events in the recovery room and pulmonary complications (defined by a 5-point [0-4; 0= best to 4= worst] outcome score) on postoperative Days 1, 3, and 7 were compared between groups. Results: Data from 168 patients aged 80 (4) yr were analysed; SUG vs NEO resulted in a reduced probability (0.052 vs 0.122) of increased pulmonary outcome score (impaired outcome) on postoperative Day 7, but not on Days 1 and 3. More patients in the NEO group were diagnosed with radiographically confirmed pneumonia (9.6% vs 2.4%; P=0.046). The NEO group showed a non-significant trend towards longer hospital length of stay across all individual centres (combined 9 vs 7.5 days), with a significant difference in Malaysia (6 vs 4 days; P=0.011). Conclusions: Reversal of rocuronium neuromuscular block with SUG resulted in a small, but possibly clinically relevant improvement in pulmonary outcome in a select cohort of high-risk older patients.

OBJECTIVE:To examine relationships between nipple pain scores and 24-hour milk production volumes, breastfeeding and pumping frequencies, and breastfeeding duration in women using nipple shields for persistent nipple pain. DESIGN:Secondary outcome analysis of a prospective cohort study. SETTING:Research laboratory and participants' homes. PARTICIPANTS:Twenty-five breastfeeding women (6 ± 4 weeks after birth) who used nipple shields for persistent nipple pain. METHODS:We conducted a randomized trial to investigate the primary outcome of milk transfer with and without nipple shields among participants with and without nipple pain. Here, we report secondary outcomes of associations between 24-hour milk production, breastfeeding and pumping frequencies, breastfeeding durations, and intake in participants using a nipple shield for nipple pain. Participants completed demographic, health and breastfeeding questionnaires and, at two monitored breastfeeding sessions, completed a pain visual analogue scale and Brief Pain Inventory-Short Form (BPI-SF; total and subscale scores for pain interference with General Activity, Mood, Sleep, and Breastfeeding). Milk production (milliliters per 24 hours), feed volumes, and percentage of available milk removed were calculated from data and milk samples obtained by participants over one 24-hour period and at study visits. Participants logged 24-hour data on a customized research website. We used descriptive statistics as well as simple and multiple linear regression for analyses. RESULTS:Milk production and feeding duration were not associated with nipple pain scores (visual analogue scale: p = .80, BPI-SF: p = .44). An increase in BPI-SF Breastfeeding subscale score of 1 unit, indicating pain interference with breastfeeding, was associated with a 0.28 decrease in 24-hour breastfeeding frequency (p = .02) and an 18.8-ml decrease in 24-hour breastfeeding intake (p = .04). CONCLUSION:Persistent nipple pain was associated with reduced breastfeeding frequency; therefore, continuing professional support is required to ensure adequate milk removal and pain management.

BACKGROUND:In disease mapping, fine-resolution spatial health data are routinely aggregated for various reasons, for example to protect privacy. Usually, such aggregation occurs only once, resulting in 'single-aggregation disease maps' whose representation of the underlying data depends on the chosen set of aggregation units. This dependence is described by the modifiable areal unit problem (MAUP). Despite an extensive literature, in practice, the MAUP is rarely acknowledged, including in disease mapping. Further, despite single-aggregation disease maps being widely relied upon to guide distribution of healthcare resources, potential inefficiencies arising due to the impact of the MAUP on such maps have not previously been investigated.RESULTS:We introduce the overlay aggregation method (OAM) for disease mapping. This method avoids dependence on any single set of aggregate-level mapping units through incorporating information from many different sets. We characterise OAM as a novel smoothing technique and show how its use results in potentially dramatic improvements in resource allocation efficiency over single-aggregation maps. We demonstrate these findings in a simulation context and through applying OAM to a real-world dataset: ischaemic stroke hospital admissions in Perth, Western Australia, in 2016.CONCLUSIONS:The ongoing, widespread lack of acknowledgement of the MAUP in disease mapping suggests that unawareness of its impact is extensive or that impact is underestimated. Routine implementation of OAM can help avoid resource allocation inefficiencies associated with this phenomenon. Our findings have immediate worldwide implications wherever single-aggregation disease maps are used to guide health policy planning and service delivery.

Neocortical Aβ-amyloid deposition, one of the hallmark pathologic features of Alzheimer's disease (AD), begins decades prior to the presence of clinical symptoms. As clinical trials move to secondary and even primary prevention, understanding the rates of neocortical Aβ-amyloid deposition and the age at which Aβ-amyloid deposition becomes abnormal is crucial for optimizing the timing of these trials. As APOE-ε4 carriage is thought to modulate the age of clinical onset, it is also important to understand the impact of APOE-ε4 carriage on the age at which the neocortical Aβ-amyloid deposition becomes abnormal. Here, we show that, for 455 participants with over 3 years of follow-up, abnormal levels of neocortical Aβ-amyloid were reached on average at age 72 (66.5-77.1). The APOE-ε4 carriers reached abnormal levels earlier at age 63 (59.6-70.3); however, noncarriers reached the threshold later at age 78 (76.1-84.4). No differences in the rates of deposition were observed between APOE-ε4 carriers and noncarriers after abnormal Aβ-amyloid levels had been reached. These results suggest that primary and secondary prevention trials, looking to recruit at the earliest stages of disease, should target APOE-ε4 carriers between the ages of 60 and 66 and noncarriers between the ages of 76 and 84.

The sum of forecasts of disaggregated time series is often required to equal the forecast of the aggregate, giving a set of coherent forecasts. The least squares solution for finding coherent forecasts uses a reconciliation approach known as MinT, proposed by Wickramasuriya, Athanasopoulos, and Hyndman (2019). The MinT approach and its variants do not guarantee that the coherent forecasts are non-negative, even when all of the original forecasts are non-negative in nature. This has become a serious issue in applications that are inherently non-negative such as with sales data or tourism numbers. While overcoming this difficulty, we reconsider the least squares minimization problem with non-negativity constraints to ensure that the coherent forecasts are strictly non-negative. The constrained quadratic programming problem is solved using three algorithms. They are the block principal pivoting (BPV) algorithm, projected conjugate gradient (PCG) algorithm, and scaled gradient projection algorithm. A Monte Carlo simulation is performed to evaluate the computational performances of these algorithms as the number of time series increases. The results demonstrate that the BPV algorithm clearly outperforms the rest, and PCG is the second best. The superior performance of the BPV algorithm can be partially attributed to the alternative representation of the weight matrix in the MinT approach. An empirical investigation is carried out to assess the impact of imposing non-negativity constraints on forecast reconciliation over the unconstrained method. It is observed that slight gains in forecast accuracy have occurred at the most disaggregated level. At the aggregated level, slight losses are also observed. Although the gains or losses are negligible, the procedure plays an important role in decision and policy implementation processes.

This chapter presents methodology for estimating the posterior distribution of regression models subject to shape constraints. There is a specific focus on estimating and performing covariate selection for monotonic polynomials, however the computational and methodological techniques are more widely applicable. We demonstrate our methodology on a number of simulated and real-world data sets. Our covariate selection code is available as an R package at https://github.com/hhau/rjmonopoly.

We provide a method for fitting monotone polynomials to data with both fixed and random effects. In pursuit of such a method, a novel approach to least squares regression is proposed for models with functional constraints. The new method is able to fit models with constrained parameter spaces that are closed and convex, and is used in conjunction with an expectation–maximisation algorithm to fit monotone polynomials with mixed effects. The resulting mixed effects models have constrained mean curves and have the flexibility to include either unconstrained or constrained subject-specific curves. This new methodology is demonstrated on real-world repeated measures data with an application from sleep science. Code to fit the methods described in this paper is available online.