Associations between infant temperament and early feeding practices. A cross-sectional study of Australian mother-infant dyads from the NOURISH randomised controlled trial

The purpose of this study was to investigate the association between temperament in Australian infants aged 2–7 months and feeding practices of their first-time mothers (n=698). Associations between feeding practices and beliefs (Infant Feeding Questionnaire) and infant temperament (easy-difficult continuous scale from the Short Temperament Scale for Infants) were tested using linear and binary logistic regression models adjusted for a comprehensive range of covariates. Mothers of infants with a more difficult temperament reported a lower awareness of infant cues, were more likely to use food to calm and reported high concern about overweight and underweight. The covariate maternal depression score largely mirrored these associations. Infant temperament may be an important variable to consider in future research on the prevention of childhood obesity. In practice, mothers of temperamentally difficult infants may need targeted feeding advice to minimise the adoption of undesirable feeding practices.

Associations exist between food insecurity, poor diet, chronic illness and obesity among an Australian population

Food insecurity is the limited availability of, or access to, sufficient amounts of nutritious, culturally-appropriate and safe foods, or the inability to access such foods by socially-acceptable means. Evidence from the United States and Canada suggests that food insecurity may be associated with poor dietary intakes, obesity, and chronic disease including depression and diabetes, thus constituting a significant public health issue. Currently, no existing studies have investigated the dietary and health factors associated with food insecurity among the general Australian population. The current study investigated the potential associations between food insecurity, diet and health among Australian adults (18 years and over) participating in the cross-sectional National Health Survey (n = 19,500). Data were analysed by logistic regression adjusting for sociodemographic covariates. Those from food insecure households were 50% less likely to consume the recommended number of servings of fruit, 60% more likely to report poor health and experienced a 6-fold increase in the risk of severe depressive disorders, compared to their food secure counterparts. Furthermore, food insecurity was associated with a 50% increase in the risk of being diagnosed with ‘high sugar levels’. Finally, women from food insecure households were 30% more likely to be obese compared to their food secure counterparts. These findings suggest that food insecurity may play an important role in preventing adherence with national dietary recommendations, and may increase the risk of obesity and chronic illness. This has important implications for both clinical practice, and the development of interventions and policy to address food insecurity.

Toddlers’ food preferences : the impact of novel food exposure, maternal preferences and food neophobia

Food preferences have been identified as a key determinant of children’s food acceptance and consumption. The aim of this study was to identify factors that influence children’s liking for fruits, vegetables and non-core foods. Participants were Australian mothers (median age at delivery=31 years, 18-46 years) and their two-year-old children (M=25 months, SD=1 month; 52% female) allocated to the control group (N=230) of the NOURISH RCT. The effects of repeated exposure to new foods, maternal food preferences and child food neophobia on toddlers’ liking of vegetables, fruits and non-core foods and the proportion never tried were examined via hierarchical regression models; adjusting for key maternal (age, BMI, education) and child covariates (birth weight Z-score, gender), duration of breastfeeding and age of introduction to solids. Maternal preferences corresponded with child preferences. Food neophobia among toddlers was associated with liking fewer vegetables and fruits, and trying fewer vegetables. Number of repeated exposures to new food was not significantly associated with food liking at this age. Results highlight the need to: (i) encourage parents to offer a wide range of foods, regardless of their own food preferences, and (ii) provide parents with guidance on managing food neophobia.

Does residential dissonance impact residential mobility?

This research identifies residential mobility behaviour impacts of residential dissonance in Transit Oriented Developments (TODs) vs. non-TODs in Brisbane, Australia. Based on the characteristics of living environments (density, diversity, connectivity, and accessibility) and the travel preferences of 4545 individuals, respondents in 2009 were classified into one of four categories including: TOD consonants, TOD dissonants, non-TOD dissonants, and non-TOD consonants. Binary logistic regression analyses were employed to identify residential mobility behaviour of groups between 2009 and 2011; controlling for time varying covariates. The findings show that both TOD dissonants and TOD consonants move residences at an equal rate. However, TOD dissonants are more likely to move residences to their preferred non-TOD areas. In contrast, non-TOD dissonants not only moved residences at a lower rate, but their rate of mobility to their preferred TOD neighbourhood is also significantly lower due to costs and other associated factors. The findings suggest that discrete land use policy development is required to integrate non-TOD dissonant and TOD dissonant behaviours to support TOD development in Brisbane.

Asset health prediction using the explicit hazard model

The ability to estimate the asset reliability and the probability of failure is critical to reducing maintenance costs, operation downtime, and safety hazards. Predicting the survival time and the probability of failure in future time is an indispensable requirement in prognostics and asset health management. In traditional reliability models, the lifetime of an asset is estimated using failure event data, alone; however, statistically sufficient failure event data are often difficult to attain in real-life situations due to poor data management, effective preventive maintenance, and the small population of identical assets in use. Condition indicators and operating environment indicators are two types of covariate data that are normally obtained in addition to failure event and suspended data. These data contain significant information about the state and health of an asset. Condition indicators reflect the level of degradation of assets while operating environment indicators accelerate or decelerate the lifetime of assets. When these data are available, an alternative approach to the traditional reliability analysis is the modelling of condition indicators and operating environment indicators and their failure-generating mechanisms using a covariate-based hazard model. The literature review indicates that a number of covariate-based hazard models have been developed. All of these existing covariate-based hazard models were developed based on the principle theory of the Proportional Hazard Model (PHM). However, most of these models have not attracted much attention in the field of machinery prognostics. Moreover, due to the prominence of PHM, attempts at developing alternative models, to some extent, have been stifled, although a number of alternative models to PHM have been suggested. The existing covariate-based hazard models neglect to fully utilise three types of asset health information (including failure event data (i.e. observed and/or suspended), condition data, and operating environment data) into a model to have more effective hazard and reliability predictions. In addition, current research shows that condition indicators and operating environment indicators have different characteristics and they are non-homogeneous covariate data. Condition indicators act as response variables (or dependent variables) whereas operating environment indicators act as explanatory variables (or independent variables). However, these non-homogenous covariate data were modelled in the same way for hazard prediction in the existing covariate-based hazard models. The related and yet more imperative question is how both of these indicators should be effectively modelled and integrated into the covariate-based hazard model. This work presents a new approach for addressing the aforementioned challenges. The new covariate-based hazard model, which termed as Explicit Hazard Model (EHM), explicitly and effectively incorporates all three available asset health information into the modelling of hazard and reliability predictions and also drives the relationship between actual asset health and condition measurements as well as operating environment measurements. The theoretical development of the model and its parameter estimation method are demonstrated in this work. EHM assumes that the baseline hazard is a function of the both time and condition indicators. Condition indicators provide information about the health condition of an asset; therefore they update and reform the baseline hazard of EHM according to the health state of asset at given time t. Some examples of condition indicators are the vibration of rotating machinery, the level of metal particles in engine oil analysis, and wear in a component, to name but a few. Operating environment indicators in this model are failure accelerators and/or decelerators that are included in the covariate function of EHM and may increase or decrease the value of the hazard from the baseline hazard. These indicators caused by the environment in which an asset operates, and that have not been explicitly identified by the condition indicators (e.g. Loads, environmental stresses, and other dynamically changing environment factors). While the effects of operating environment indicators could be nought in EHM; condition indicators could emerge because these indicators are observed and measured as long as an asset is operational and survived. EHM has several advantages over the existing covariate-based hazard models. One is this model utilises three different sources of asset health data (i.e. population characteristics, condition indicators, and operating environment indicators) to effectively predict hazard and reliability. Another is that EHM explicitly investigates the relationship between condition and operating environment indicators associated with the hazard of an asset. Furthermore, the proportionality assumption, which most of the covariate-based hazard models suffer from it, does not exist in EHM. According to the sample size of failure/suspension times, EHM is extended into two forms: semi-parametric and non-parametric. The semi-parametric EHM assumes a specified lifetime distribution (i.e. Weibull distribution) in the form of the baseline hazard. However, for more industry applications, due to sparse failure event data of assets, the analysis of such data often involves complex distributional shapes about which little is known. Therefore, to avoid the restrictive assumption of the semi-parametric EHM about assuming a specified lifetime distribution for failure event histories, the non-parametric EHM, which is a distribution free model, has been developed. The development of EHM into two forms is another merit of the model. A case study was conducted using laboratory experiment data to validate the practicality of the both semi-parametric and non-parametric EHMs. The performance of the newly-developed models is appraised using the comparison amongst the estimated results of these models and the other existing covariate-based hazard models. The comparison results demonstrated that both the semi-parametric and non-parametric EHMs outperform the existing covariate-based hazard models. Future research directions regarding to the new parameter estimation method in the case of time-dependent effects of covariates and missing data, application of EHM in both repairable and non-repairable systems using field data, and a decision support model in which linked to the estimated reliability results, are also identified.

Years lived with disability (YLDs) for 1160 sequelae of 289 diseases and injuries 1990–2010 : a systematic analysis for the Global Burden of Disease Study 2010

Background Non-fatal health outcomes from diseases and injuries are a crucial consideration in the promotion and monitoring of individual and population health. The Global Burden of Disease (GBD) studies done in 1990 and 2000 have been the only studies to quantify non-fatal health outcomes across an exhaustive set of disorders at the global and regional level. Neither effort quantified uncertainty in prevalence or years lived with disability (YLDs). Methods Of the 291 diseases and injuries in the GBD cause list, 289 cause disability. For 1160 sequelae of the 289 diseases and injuries, we undertook a systematic analysis of prevalence, incidence, remission, duration, and excess mortality. Sources included published studies, case notification, population-based cancer registries, other disease registries, antenatal clinic serosurveillance, hospital discharge data, ambulatory care data, household surveys, other surveys, and cohort studies. For most sequelae, we used a Bayesian meta-regression method, DisMod-MR, designed to address key limitations in descriptive epidemiological data, including missing data, inconsistency, and large methodological variation between data sources. For some disorders, we used natural history models, geospatial models, back-calculation models (models calculating incidence from population mortality rates and case fatality), or registration completeness models (models adjusting for incomplete registration with health-system access and other covariates). Disability weights for 220 unique health states were used to capture the severity of health loss. YLDs by cause at age, sex, country, and year levels were adjusted for comorbidity with simulation methods. We included uncertainty estimates at all stages of the analysis. Findings Global prevalence for all ages combined in 2010 across the 1160 sequelae ranged from fewer than one case per 1 million people to 350 000 cases per 1 million people. Prevalence and severity of health loss were weakly correlated (correlation coefficient −0·37). In 2010, there were 777 million YLDs from all causes, up from 583 million in 1990. The main contributors to global YLDs were mental and behavioural disorders, musculoskeletal disorders, and diabetes or endocrine diseases. The leading specific causes of YLDs were much the same in 2010 as they were in 1990: low back pain, major depressive disorder, iron-deficiency anaemia, neck pain, chronic obstructive pulmonary disease, anxiety disorders, migraine, diabetes, and falls. Age-specific prevalence of YLDs increased with age in all regions and has decreased slightly from 1990 to 2010. Regional patterns of the leading causes of YLDs were more similar compared with years of life lost due to premature mortality. Neglected tropical diseases, HIV/AIDS, tuberculosis, malaria, and anaemia were important causes of YLDs in sub-Saharan Africa. Interpretation Rates of YLDs per 100 000 people have remained largely constant over time but rise steadily with age. Population growth and ageing have increased YLD numbers and crude rates over the past two decades. Prevalences of the most common causes of YLDs, such as mental and behavioural disorders and musculoskeletal disorders, have not decreased. Health systems will need to address the needs of the rising numbers of individuals with a range of disorders that largely cause disability but not mortality. Quantification of the burden of non-fatal health outcomes will be crucial to understand how well health systems are responding to these challenges. Effective and affordable strategies to deal with this rising burden are an urgent priority for health systems in most parts of the world. Funding Bill & Melinda Gates Foundation.

An exploratory study of associations between Australian-Indian mothers’ use of controlling feeding practices, concerns and perceptions of children’s weight and children’s picky eating

Aim This cross-sectional study explores associations between migrant Indian mothers’ use of controlling feeding practices (pressure to eat, restriction and monitoring) and their concerns and perceptions regarding their children’s weight and picky eating behaviour. Methods Two hundred and thirty mothers with children aged 1-5 years, residing in Australia for 1-8 years, participated by completing a self-reported questionnaire. Results Perceptions and concerns regarding children’s weight were not associated with any of the controlling feeding practices. A positive association was noted between pressure feeding and perceptions of pickiness after adjusting for covariates: children’s age, gender and weight-for-age Z-score. Girls, older children, and children with higher weight-for-age z scores were pressure fed to a greater extent. Conclusions This study supports the generalisation of findings from Caucasian literature that pressure feeding and perceptions of pickiness are positively related.

Prediction of age at menopause from assessment of ovarian reserve may be improved by using body mass index and smoking status

Objective: Menopause is the consequence of exhaustion of the ovarian follicular pool. AMH, an indirect hormonal marker of ovarian reserve, has been recently proposed as a predictor for age at menopause. Since BMI and smoking status are relevant independent factors associated with age at menopause we evaluated whether a model including all three of these variables could improve AMH-based prediction of age at menopause. Methods: In the present cohort study, participants were 375 eumenorrheic women aged 19–44 years and a sample of 2,635 Italian menopausal women. AMH values were obtained from the eumenorrheic women. Results: Regression analysis of the AMH data showed that a quadratic function of age provided a good description of these data plotted on a logarithmic scale, with a distribution of residual deviates that was not normal but showed significant leftskewness. Under the hypothesis that menopause can be predicted by AMH dropping below a critical threshold, a model predicting menopausal age was constructed from the AMH regression model and applied to the data on menopause. With the AMH threshold dependent on the covariates BMI and smoking status, the effects of these covariates were shown to be highly significant. Conclusions: In the present study we confirmed the good level of conformity between the distributions of observed and AMH-predicted ages at menopause, and showed that using BMI and smoking status as additional variables improves AMH-based prediction of age at menopause.

Sleepless nights : the effect of socioeconomic status, physical activity, and lifestyle factors on sleep quality in a large cohort of Australian women

The aims of this study were to examine: (1) the association between sociodemographic and lifestyle factors and sleep quality in a population-based cohort of Australian women and (2) possible influence of reproductive status and mental and physical health factors on these associations. Data on 3,655 women (mean age046.6 years, range 34.3–67.4) were obtained from the Mater Hospital University of Queensland Study of Pregnancy for this cross-sectional study. Self-rated sleep quality was assessed using the Pittsburgh Sleep Quality Index. For the purpose of this study, two cutoff points (scores 5 and 10) were used to divide women into three categories: normal (65.2 %), moderately poor (26.4 %), and very poor sleep quality (8.5 %). Other covariates were measured at 21-year follow-up as well. After adjusting for reproductive status, mental and physical health, there were significant associations between moderately poor sleep quality and education and between very poor sleep quality and unemployment, both measures of socioeconomic status. In addition, work-related exertion was associated with increased rates of moderately poor sleep quality, whereas those women undertaking moderate exercise were less likely to experience very poor sleep quality. Independent associations between sociodemographic factors and exercise with moderately poor and very poor sleep quality were identified. These findings demonstrate the dynamic nature of the association between exercise/exertion, socioeconomic status, and sleep quality and highlight the importance of taking these into consideration when dealing with issues of poor sleep quality in women.

Differences in the symptom experience of older versus younger oncology outpatients : a cross-sectional study

Background: Mortality rates for cancer are decreasing in patients under 60 and increasing in those over 60 years of age. The reasons for these differences in mortality rates remain poorly understood. One explanation may be that older patients received substandard treatment because of concerns about adverse effects. Given the paucity of research on the multiple dimensions of the symptom experience in older oncology patients, the purpose of this study was to evaluate for differences in ratings of symptom occurrence, severity, frequency, and distress between younger (< 60 years) and older ( ≥ 60 years) adults undergoing cancer treatment. We hypothesized that older patients would have significantly lower ratings on four symptom dimensions. Methods: Data from two studies in the United States and one study in Australia were combined to conduct this analysis. All three studies used the MSAS to evaluate the occurrence, severity, frequency, and distress of 32 symptoms. Results: Data from 593 oncology outpatients receiving active treatment for their cancer (i.e., 44.4% were < 60 years and 55.6% were ≥ 60 years of age) were evaluated. Of the 32 MSAS symptoms, after controlling for significant covariates, older patients reported significantly lower occurrence rates for 15 (46.9%) symptoms, lower severity ratings for 6 (18.9%) symptoms, lower frequency ratings for 4 (12.5%) symptoms, and lower distress ratings for 14 (43.8%) symptoms. Conclusions: This study is the first to evaluate for differences in multiple dimensions of symptom experience in older oncology patients. For almost 50% of the MSAS symptoms, older patients reported significantly lower occurrence rates. While fewer age-related differences were found in ratings of symptom severity, frequency, and distress, a similar pattern was found across all three dimensions. Future research needs to focus on a detailed evaluation of patient and clinical characteristics (i.e., type and dose of treatment) that explain the differences in symptom experience identified in this study.

Does residential dissonance impact residential mobility?

This research identifies residential mobility behaviour impacts of residential dissonance in Transit Oriented Developments (TODs) vs. non-TODs in Brisbane, Australia. Based on the characteristics of living environments (density, diversity, connectivity, and accessibility) and the travel preferences of 4545 individuals, respondents in 2009 were classified into one of four categories including: TOD consonants, TOD dissonants, non-TOD dissonants, and non-TOD consonants. Binary logistic regression analyses were employed to identify residential mobility behaviour of groups between 2009 and 2011; controlling for time varying covariates. The findings show that both TOD dissonants and TOD consonants move residences at an equal rate. However, TOD dissonants are more likely to move residences to their preferred non-TOD areas. In contrast, non-TOD dissonants not only moved residences at a lower rate, but their rate of mobility to their preferred TOD neighbourhood is also significantly lower due to costs and other associated factors. The findings suggest that discrete land use policy development is required to integrate non-TOD dissonant and TOD dissonant behaviours to support TOD development in Brisbane.

Feeding attitudes, practices and traditional dietary beliefs of Chinese mothers with young children in Australia : a mixed methods study

Background and Objectives Obesity and some dietary related diseases are emerging health problems among Chinese immigrants and their children in developed countries. These health problems are closely linked to eating habits, which are established in the early years of life. Young children’s eating habits are likely to persist into later childhood and youth. Family environment and parental feeding practices have a strong effect on young children’s eating habits. Little information is available on the early feeding practices of Chinese mothers in Australia. The aim of this study was to understand the dietary beliefs, feeding attitudes and practices of Chinese mothers with young children who were recent immigrants to Australia. Methods Using a sequential explanatory design, this mixed methods study consisted of two distinct phases. Phase 1 (quantitative): 254 Chinese immigrant mothers of children aged 12 to 59 months completed a cross-sectional survey. The psychometric properties and factor structure of a Chinese version of the Child Feeding Questionnaire (CFQ, by Birch et al. 2001) were assessed and used to measure specific maternal feeding attitudes and controlling feeding practices. Other questions were developed from the literature and used to explore maternal traditional dietary beliefs and feeding practices related to their beliefs, perceptions of picky eating in children and a range of socioeconomic and acculturation factors. Phase 2 (qualitative): 21 mothers took part in a follow-up telephone interview to assist in explaining and interpreting some significant findings obtained in the first phase. Results Chinese mothers held strong traditional dietary beliefs and fed their children according to these beliefs. However, children’s consumption of non-core foods was high. Both traditional Chinese and Australian style foods were consumed by their children. Confirmatory factor analysis revealed that the original 7-factor model of the CFQ provided an acceptable fit to the data with minor modification. However, an alternative model with eight constructs in which two items related to using food rewards were separated from the original restriction construct, not only provided an acceptable fit to the data, but also improved the conceptual clarity of the constructs. The latter model included 24 items loading onto the following eight constructs: restriction, pressure to eat, monitoring, use of food rewards, perceived responsibility, perception of own weight, perception of child’s weight, and concern about child becoming overweight. The internal consistency of the constructs was acceptable or desirable (Cronbach’s α = .60 - .93). Mothers reported low levels of concern about their child overeating or becoming overweight, but high levels of controlling feeding practices: restriction, monitoring, pressure to eat and use of food rewards. More than one quarter of mothers misinterpreted their child’s weight status (based on mothers’ self-reported data). In addition, mothers’ controlling feeding practices independently predicted half of the variance and explained 16% of the variance in child weight status: pressuring the child to eat was negatively associated with child weight status (β = -0.30, p < .01) and using food rewards was positively associated with child weight status (β = 0.20, p < .05) after adjusting for maternal and child covariates. Monitoring and restriction were not associated with child weight status. Mothers’ perceptions of their child’s weight were positively associated with child weight status (β = 0.33, p < .01). Moreover, mothers reported that they mostly decided what (65%) and how much (80%) food their child ate. Mothers who decided what food their child ate were more likely to monitor (β = -0.17, p < .05) and restrict (β = -0.17, p < .05) their child’s food consumption. Mothers who let their child decide how much food their child ate were less likely to pressure their child to eat (β = -0.38, p < .01) and use food rewards (β = -0.24, p < .01). Mothers’ perceptions of picky eating behaviour were positively associated with their use of pressure (β = 0.21, p < .01) and negatively associated with monitoring (β = -0.16, p < .05) and perceptions of their child’s weight status (β = -0.13, p < .05). Qualitative data showed that pressuring to eat, monitoring and restriction of the child’s food consumption were common practices among these mothers. However, mothers stated that their motivation for monitoring and restricting was to ensure the child’s general health. Mothers’ understandings of picky eating behaviour in their children were consistent with the literature and they reported multiple feeding strategies to deal with it. Conclusion Chinese immigrant mothers demonstrated strong traditional dietary beliefs, a low level of concern for child weight, misperceptions of child weight status, and a high overall level of control in child feeding in this study. The Chinese version of the CFQ, which consists of eight constructs and distinguishes between the constructs using food rewards and restriction, is an appropriate instrument to assess feeding attitudes and controlling feeding practices among Chinese immigrant mothers of young children in Australia. Mothers’ feeding attitudes and practices were associated with children’s weight status and mothers’ perceptions of picky eating behaviour in children after adjusting for a range of socio-demographic maternal and child characteristics. Monitoring and restriction of children’s food consumption according to food selection may be positive feeding practices, whereas pressuring to eat and using food rewards appeared to be negative feeding practices in this study. In addition, the results suggest that these young children have high exposure to energy-dense, nutrient-poor food. There is a need to develop and implement nutrition interventions to improve maternal feeding practices and the dietary quality among children of Chinese immigrant mothers in Australia.

Bayesian survival analysis using gene expression

This thesis developed and applied Bayesian models for the analysis of survival data. The gene expression was considered as explanatory variables within the Bayesian survival model which can be considered the new contribution in the analysis of such data. The censoring factor that is inherent of survival data has also been addressed in terms of its impact on the fitting of a finite mixture of Weibull distribution with and without covariates. To investigate this, simulation study were carried out under several censoring percentages. Censoring percentage as high as 80% is acceptable here as the work involved high dimensional data. Lastly the Bayesian model averaging approach was developed to incorporate model uncertainty in the prediction of survival.

Depressive symptoms during pregnancy: Exploring the role of sitting

Statement of problem: Studies exploring relationships between sitting and mental health have been conducted in child and adult, but not pregnant populations. Depression during pregnancy is associated with deleterious outcomes for mothers and children, and shortcomings have been identified in current management strategies. Modifiable lifestyle behaviors may provide more acceptable alternatives to current management strategies if shown to be important. The aim of this study was to explore the relationship between sitting behavior and depressive symptoms in a population of pregnant Australian women. Methods: This pilot cross-sectional study included 81 pregnant women in Brisbane, Australia. Depressive symptoms were measured using the Hospital Anxiety and Depression Scale (HADS). Sitting behavior was measured using the Australian Women's Activity Survey (AWAS). Several potential covariates were also assessed. Linear regression analyses were used to explore the relationship between sitting and depressive symptoms, whilst controlling for known covariates. Results: The model investigating “total sitting time” showed no association with depressive symptoms (F = .77, p = 0.38). The model investigating “planned leisure sitting time” was statistically significant (F = 4.42, p = 0.04): significant contributors to the model variance were HADS anxiety score (p = 0.003) and number of existing children (p = 0.02). “Planned leisure sitting time” showed a statistical trend toward significance (p = 0.06). Conclusions: This study suggests further investigation of the relationship between sitting, particularly planned leisure sitting, and depression during pregnancy is warranted. Future research should include a larger sample and an objective measure of leisure time sitting.

Spatio-temporal modelling of ultrafine particle number concentration

This thesis developed semi-parametric regression models for estimating the spatio-temporal distribution of outdoor airborne ultrafine particle number concentration (PNC). The models developed incorporate multivariate penalised splines and random walks and autoregressive errors in order to estimate non-linear functions of space, time and other covariates. The models were applied to data from the "Ultrafine Particles from Traffic Emissions and Child" project in Brisbane, Australia, and to longitudinal measurements of air quality in Helsinki, Finland. The spline and random walk aspects of the models reveal how the daily trend in PNC changes over the year in Helsinki and the similarities and differences in the daily and weekly trends across multiple primary schools in Brisbane. Midday peaks in PNC in Brisbane locations are attributed to new particle formation events at the Port of Brisbane and Brisbane Airport.