The longitudinal associations between ambient air pollution exposure and dementia in the UK: results from the cognitive function and ageing study II and Wales.

BACKGROUND: Air pollution has been recognised as a potential risk factor for dementia. Yet recent epidemiological research shows mixed evidence. The aim of this study is to investigate the longitudinal associations between ambient air pollution exposure and dementia in older people across five urban and rural areas in the UK. METHODS: This study was based on two population-based cohort studies of 11329 people aged ≥ 65 in the Cognitive Function and Ageing Study II (2008-2011) and Wales (2011-2013). An algorithmic diagnosis method was used to identify dementia cases. Annual concentrations of four air pollutants (NO2, O3, PM10, PM2.5) were modelled for the year 2012 and linked via the participants' postcodes. Multistate modelling was used to examine the effects of exposure to air pollutants on incident dementia incorporating death and adjusting for sociodemographic factors and area deprivation. A random-effect meta-analysis was carried out to summarise results from the current and nine existing cohort studies. RESULTS: Higher exposure levels of NO2 (HR: 1.04; 95% CI: 0.94, 1.14), O3 (HR: 0.90; 95% CI: 0.70, 1.15), PM10 (HR: 1.17; 95% CI: 0.86, 1.58), PM2.5 (HR: 1.41; 95% CI: 0.71, 2.79) were not strongly associated with dementia in the two UK-based cohorts. Inconsistent directions and strengths of the associations were observed across the two cohorts, five areas, and nine existing studies. CONCLUSIONS: In contrast to the literature, this study did not find clear associations between air pollution and dementia. Future research needs to investigate how methodological and contextual factors can affect evidence in this field and clarity the influence of air pollution exposure on cognitive health over the lifecourse.

Physical activity, sedentary behaviour, and cognitive function among older adults: A bibliometric analysis from 2004 to 2024.

Because of population ageing, there will be a vast increase in the prevalence of cognitive decline and dementia. Physical activity and sedentary behaviour have been identified as modifiable lifestyle behaviours associated with these cognitive conditions. Therefore, the aim of this bibliometric analysis is to reveal the knowledge structure of the field of physical activity, sedentary behaviour, and cognitive function among older adults from 2004 to 2024, and to predict emerging research trends. A total of 1290 publications were retrieved from the Web of Science Core Collection. CiteSpace and VOSviewer were applied to conduct performance analysis, science mapping, and enrichment. T. Liu-Ambrose was the most prolific author (39 publications), and the University of British Columbia was the most prolific institution (48 publications). The USA, China, and Canada were the three most productive countries with 392, 174, and 136 publications respectively. Two research trends revealed the knowledge structure of this field, including the shift from evaluating the effectiveness of interventions on cognitive function to evaluating the effectiveness of interventions on other health-related outcomes, as well as an expansion of research on the role of physical activity and sedentary behaviour in the context of healthy ageing. Sleep, sedentary behaviour, and virtual reality may be emerging research trends and may predict directions for future research. Collectively, this bibliometric analysis provides a one-step overview of the knowledge structure in this field for researchers and other stakeholders, as well as a reference for future research.

Network Representation of fMRI Data Using Visibility Graphs: The Impact of Motion and Test-Retest Reliability.

Visibility graphs provide a novel approach for analysing time-series data. Graph theoretical analysis of visibility graphs can provide new features for data mining applications in fMRI. However, visibility graphs features have not been used widely in the field of neuroscience. This is likely due to a lack of understanding of their robustness in the presence of noise (e.g., motion) and their test-retest reliability. In this study, we investigated visibility graph properties of fMRI data in the human connectome project (N = 1010) and tested their sensitivity to motion and test-retest reliability. We also characterised the strength of connectivity obtained using degree synchrony of visibility graphs. We found that strong correlation (r > 0.5) between visibility graph properties, such as the number of communities and average degrees, and motion in the fMRI data. The test-retest reliability (Intraclass correlation coefficient (ICC)) of graph theoretical features was high for the average degrees (0.74, 95% CI = [0.73, 0.75]), and moderate for clustering coefficient (0.43, 95% CI = [0.41, 0.44]) and average path length (0.41, 95% CI = [0.38, 0.44]). Functional connectivity between brain regions was measured by correlating the visibility graph degrees. However, the strength of correlation was found to be moderate to low (r < 0.35). These findings suggest that even small movement in fMRI data can strongly influence robustness and reliability of visibility graph features, thus, requiring robust motion correction strategies prior to data analysis. Further studies are necessary for better understanding of the potential application of visibility graph features in fMRI.

Cost-effectiveness of reducing children's sedentary time and increasing physical activity at school: the Transform-Us! intervention.

BACKGROUND: Improving physical activity and reducing sedentary behavior represent important areas for intervention in childhood in order to reduce the burden of chronic disease related to obesity and physical inactivity in later life. This paper aims to determine the cost-effectiveness of a multi-arm primary school-based intervention to increase physical activity and/or reduce sedentary time in 8-9 year old children (Transform-Us!). METHODS: Modelled cost-utility analysis, using costs and effects from a cluster randomized controlled trial of a 30-month intervention that used pedagogical and environmental strategies to reduce and break up sedentary behaviour (SB-I), promote physical activity (PA-I), or a combined approach (PA + SB-I), compared to current practice. A validated multiple-cohort lifetable model (ACE-Obesity Policy model) estimated the obesity and physical activity-related health outcomes (measured as change in body mass index and change in metabolic equivalent task minutes respectively) and healthcare cost-savings over the cohort's lifetime from the public-payer perspective, assuming the intervention was delivered to all 8-9 year old children attending Australian Government primary schools. Sensitivity analyses tested the impact on cost-effectiveness of varying key input parameters, including maintenance of intervention effect assumptions. RESULTS: Cost-effectiveness results demonstrated that, when compared to control schools, the PA-I and SB-I intervention arms were "dominant", meaning that they resulted in net health benefits and healthcare cost-savings if the intervention effects were maintained. When the costs and effects of these intervention arms were extrapolated to the Australian population, results suggested significant potential as obesity prevention measures (PA-I: 60,780 HALYs saved (95% UI 15,007-109,413), healthcare cost-savings AUD641M (95% UI AUD165M-$1.1B); SB-I: 61,126 HALYs saved (95% UI 11,770 - 111,249), healthcare cost-savings AUD654M (95% UI AUD126M-1.2B)). The PA-I and SB-I interventions remained cost-effective in sensitivity analysis, assuming the full decay of intervention effect after 10 years. CONCLUSIONS: The PA-I and SB-I Transform-Us! intervention arms represent good value for money and could lead to health benefits and healthcare cost-savings arising from the prevention of chronic disease in later life if intervention effects are sustained. TRIAL REGISTRATION: International Standard Randomized Controlled Trial Number (ISRCTN83725066). Australia and New Zealand Clinical Trials Registry Number (ACTRN12609000715279).

Cities and mental health: The role of the built environment, and environmental and lifestyle factors in Barcelona.

Built environment characteristics and related environmental exposures and behaviors have been, separately, implicated in the development of poor mental health. However, it is unclear how these factors act together in relation to mental health. We studied these factors simultaneously to evaluate the impact of the built environment, and the mediating role of environmental exposures and physical activity, on mental health, while also studying moderation by sex, age, and length of residence. We used a cross-sectional population-based sample of 3145 individuals aged 15-97 years from Barcelona, Spain. Time spent walking and mental health status were assessed with validated questionnaires, administered through a face-to-face interview. We characterized the built environment (e.g., building, population and intersection density and green space), road traffic noise, and ambient air pollution at the residential level using land cover maps, remote sensing, noise maps and land use regression models. Adjusted regression models accounting for spatial clustering were analyzed to study associations between built environment attributes and mental health, and mediation and moderation effects. Density attributes were directly or indirectly, through air pollution and less consistently through walking, associated with poor mental health. Green space indicators were associated with lower prevalence of poor mental health, partly through lower air pollution exposure and more walking. In some cases, these associations differed by sex, age or length of residence. Non-linear associations of density indicators with environmental exposures, and of particulate matter with poor mental health indicated threshold effects. We conclude that living in dense areas with high air pollution concentrations was associated with poor mental health. On the other hand, green areas with lower air pollution concentrations were protective against poor mental health. Greater urban density might benefit health, but might only do so when air pollution concentrations are low.

Prioritizing a research agenda on built environments and physical activity: a twin panel Delphi consensus process with researchers and knowledge users.

BACKGROUND: The growth of urban dwelling populations globally has led to rapid increases of research and policy initiatives addressing associations between the built environment and physical activity (PA). Given this rapid proliferation, it is important to identify priority areas and research questions for moving the field forward. The objective of this study was to identify and compare research priorities on the built environment and PA among researchers and knowledge users (e.g., policy makers, practitioners). METHODS: Between September 2022 and April 2023, a three-round, modified Delphi survey was conducted among two independent panels of international researchers (n = 38) and knowledge users (n = 23) to identify similarities and differences in perceived research priorities on the built environment and PA and generate twin 'top 10' lists of the most important research needs. RESULTS: From a broad range of self-identified issues, both panels ranked in common the most pressing research priorities including stronger study designs such as natural experiments, research that examines inequalities and inequities, establishing the cost effectiveness of interventions, safety and injuries related to engagement in active transportation (AT), and considerations for climate change and climate adaptation. Additional priorities identified by researchers included: implementation science, research that incorporates Indigenous perspectives, land-use policies, built environments that support active aging, and participatory research. Additional priorities identified by knowledge users included: built environments and PA among people living with disabilities and a need for national data on trip chaining, multi-modal travel, and non-work or school-related AT. CONCLUSIONS: Five common research priorities between the two groups emerged, including (1) to better understand causality, (2) interactions with the natural environment, (3) economic evaluations, (4) social disparities, and (5) preventable AT-related injuries. The findings may help set directions for future research, interdisciplinary and intersectoral collaborations, and funding opportunities.

Lifestyle factors as mediators of area-level socioeconomic differentials in mental health and cognitive function: the Tromsø Study.

INTRODUCTION: Low socioeconomic status (SES) is associated with poor mental health and cognitive function. Individual-level SES and area-level SES (ASES) may affect mental health and cognitive function through lifestyle. We aimed to quantify the associations of ASES with mental health and cognitive function and examine the mediating role of lifestyle behaviours independent of individual-level SES in a Norwegian population. METHODS: In this cross-sectional study, we included 7211 participants (54% women) from the seventh survey of the Tromsø Study (2015-2016) (Tromsø7). The exposure variable ASES was created by aggregating individual-level SES variables (education, income, housing ownership) from Statistics Norway at the geographical subdivision level. Tromsø7 data were used as mediators (smoking, snuff, alcohol, physical activity, diet) and outcomes (cognitive function, anxiety, depression, insomnia). Mediation and mediated moderation analysis were performed with age as a moderator, stratified by sex. RESULTS: Higher ASES was associated with better cognitive function and fewer depression and insomnia symptoms, independent of individual-level SES. These associations were mediated by smoking and physical activity. Alcohol was a mediator for depression and cognitive function in women. Age was a significant moderator of the association between ASES and global cognitive function in women. The largest total indirect effect of ASES was found for depression, with the joint effect of the mediators accounting for 36% of the total effect. CONCLUSIONS: People living in areas with lower ASES are at higher risk of poor mental health, such as depression and insomnia, and have lower cognitive function possibly due to unhealthy lifestyle (smoking, alcohol and physical inactivity).

Socioeconomic characteristics and domestic work as correlates of family satisfaction in Hong Kong mothers of young children.

BACKGROUND: Family life satisfaction is an important contributor to the mental health of mothers with young children, who are particularly vulnerable to various sources of stressors. However, there is a dearth of studies on this topic in this demographic, the determinants of which likely differ across geographical and cultural contexts. We examined indicators of maternal socioeconomic status (SES) and domestic help as correlates of family satisfaction in Hong Kong mothers of young children. METHODS: Mothers (N = 322) of young children (3-5 years old) were recruited from neighbourhoods stratified by SES and population density. They self-completed a survey containing items on socio-demographics, SES characteristics (including household income and maternal education and employment status), maternal family satisfaction and division of domestic work in the household and family. Confounder-adjusted associations of maternal SES indicators and participation in housework and childcare activities by various agents (e.g., mother, spouse, other residents) were estimated. We also estimated the moderating effects of household income on the associations between maternal employment and family satisfaction, and those of maternal employment on the associations between domestic work division and family satisfaction. RESULTS: Household income and maternal education were positively related to maternal family satisfaction. Mothers in part-time employment had lower family satisfaction than non-working mothers and mothers working full-time. The latter reported higher family satisfaction than non-working mothers only if their household income was below HK$ 15,000. Domestic work performed by non-residents was predictive of higher family satisfaction, while mothers' housework and child(ren) tutoring were predictive of lower family satisfaction. Only part-time employed mothers benefited from spouse's assistance with domestic work. The interaction effects of maternal employment status on the associations between the division of child tutoring and family satisfaction were complex. CONCLUSIONS: In Hong Kong, mothers of young children with lower education and household income, who hold a part-time job and participate in housework and child tutoring activities have the lowest levels of family satisfaction and, hence, are at higher risk of mental health problems. Spouses' and non-resident family members' participation in domestic work, as well as the establishment of more family-friendly employment practices, may help mitigate this risk. TRIAL REGISTRATION: N/A.

Improving traffic-related air pollution estimates by modelling minor road traffic volumes.

Accurately estimating annual average daily traffic (AADT) on minor roads is essential for assessing traffic-related air pollution (TRAP) exposure, particularly in areas where most people live. Our study assessed the direct and indirect external validity of three methods used to estimate AADT on minor roads in Melbourne, Australia. We estimated the minor road AADT using a fixed-value approach (assuming 600 vehicles/day) and linear and negative binomial (NB) models. The models were generated using road type, road importance index, AADT and distance of the nearest major road, population density, workplace density, and weighted road density. External measurements of traffic counts, as well as black carbon (BC) and ultrafine particles (UFP), were conducted at 201 sites for direct and indirect validation, respectively. Statistical tests included Akaike information criterion (AIC) to compare models' performance, the concordance correlation coefficient (CCC) for direct validation, and Spearman's correlation coefficient for indirect validation. Results show that 88.5% of the roads in Melbourne are minor, yet only 18.9% have AADT. The performance assessment of minor road models indicated comparable performance for both models (AIC of 1,023,686 vs. 1,058,502). In the direct validation with external traffic measurements, there was no difference between the three methods for overall minor roads. However, for minor roads within residential areas, CCC (95% confidence interval [CI]) values were -0.001 (-0.17; 0.18), 0.47 (0.32; 0.60), and 0.29 (0.18; 0.39) for the fixed-value approach, the linear model, and the NB model, respectively. In the indirect validation, we found differences only on UFP where the Spearman's correlation (95% CI) for both models and fixed-value approach were 0.50 (0.37; 0.62) and 0.34 (0.19; 0.48), respectively. In conclusion, our linear model outperformed the fixed-value approach when compared against traffic and TRAP measurements. The methodology followed in this study is relevant to locations with incomplete minor road AADT data.

Characteristics of urban neighbourhood environments and cognitive age in mid-age and older adults.

In this cross-sectional study, we examined the extent to which features of the neighbourhood natural, built, and socio-economic environments were related to cognitive age in adults (N = 3418, Mage = 61 years) in Australia. Machine learning estimated an individual's cognitive age from assessments of processing speed, verbal memory, premorbid intelligence. A 'cognitive age gap' was calculated by subtracting chronological age from predicted cognitive age and was used as a marker of cognitive age. Greater parkland availability and higher neighbourhood socio-economic status were associated with a lower cognitive age gap score in confounder- and mediator-adjusted regression models. Cross-sectional design is a limitation. Living in affluent neighbourhoods with access to parks maybe beneficial for cognitive health, although selection mechanisms may contribute to the findings.

Modelling count, bounded and skewed continuous outcomes in physical activity research: beyond linear regression models.

BACKGROUND: Inference using standard linear regression models (LMs) relies on assumptions that are rarely satisfied in practice. Substantial departures, if not addressed, have serious impacts on any inference and conclusions; potentially rendering them invalid and misleading. Count, bounded and skewed outcomes, common in physical activity research, can substantially violate LM assumptions. A common approach to handle these is to transform the outcome and apply a LM. However, a transformation may not suffice. METHODS: In this paper, we introduce the generalized linear model (GLM), a generalization of the LM, as an approach for the appropriate modelling of count and non-normally distributed (i.e., bounded and skewed) outcomes. Using data from a study of physical activity among older adults, we demonstrate appropriate methods to analyse count, bounded and skewed outcomes. RESULTS: We show how fitting an LM when inappropriate, especially for the type of outcomes commonly encountered in physical activity research, substantially impacts the analysis, inference, and conclusions compared to a GLM. CONCLUSIONS: GLMs which more appropriately model non-normally distributed response variables should be considered as more suitable approaches for managing count, bounded and skewed outcomes rather than simply relying on transformations. We recommend that physical activity researchers add the GLM to their statistical toolboxes and become aware of situations when GLMs are a better method than traditional approaches for modeling count, bounded and skewed outcomes.

Associations of home and neighborhood environments with children's physical activity in the U.S.-based Neighborhood Impact on Kids (NIK) longitudinal cohort study.

INTRODUCTION: Physical activity is important for children's health and well-being. Supportiveness for physical activity of home and neighborhood environments may affect children's PA, but most studies are cross-sectional. We examined environmental predictors of change in children's physical activity over two years. METHODS: Data were from the longitudinal, observational cohort study, 'Neighborhood Impact on Kids'. Participants were children (initially aged 6-12 years) and their parent/caregiver (n = 727 dyads) living in neighborhoods throughout San Diego County, California and King County (Seattle area), Washington, USA. Children's moderate-to-vigorous physical activity (MVPA) was measured using accelerometers at T1 (Time 1 or baseline, 2007-2009) and T2, the two-year follow-up. At T1, parents survey-reported on physical activity (PA) equipment at home and demographics. Neighborhood environment was measured using spatial data in Geographic Information Systems (intersection density; park availability) and in-person audits (informal play space near home; park-based PA facilities; land use; support for walking/cycling). Generalized additive mixed models estimated total effects, then direct effects, of environmental attributes on MVPA at T1. Two-way moderating effects of child's sex and age were examined at T1. To examine associations of environmental exposures with changes in MVPA, we estimated interaction effects of environmental attributes on the association between time and MVPA. RESULTS: On average, children accumulated 146 min/day (standard deviation or SD = 53) of MVPA at T1, and 113 (SD = 58) min/day at T2. There were no significant total or direct effects of environmental attributes on MVPA at T1, and no significant two-way interaction effects of child's age and sex for T1 MVPA. Having informal play spaces proximal to home with more amenities was associated with less MVPA decline from T1 to T2. Higher residential density, higher land use mix, and higher number of PA facilities in nearby parks were unexpectedly associated with greater MVPA decline. CONCLUSION: Higher quality informal play spaces close to home may help offset declines in MVPA during middle childhood, as they may promote unstructured active play with opportunities for parental or neighbor surveillance. Unexpectedly, environmental factors consistent with higher walkability were associated with greater declines in children's MVPA. As physical activity differs across the lifespan, so may environmental factors that facilitate it.

Transform-Us! cluster RCT: 18-month and 30-month effects on children's physical activity, sedentary time and cardiometabolic risk markers.

OBJECTIVE: To test the efficacy of the Transform-Us! school- and home-based intervention on children's physical activity (PA), sedentary behaviour (SB) and cardiometabolic risk factor profiles. METHODS: A 30-month 2×2 factorial design cluster randomised controlled trial delivered in 20 primary schools (148 Year 3 classes) in Melbourne, Australia (2010-2012), that used pedagogical and environmental strategies to reduce and break up SB, promote PA or a combined approach, compared with usual practice. Primary outcomes (accelerometry data; n=348) were assessed at baseline, 18 and 30 months. Secondary outcomes included body mass index (BMI) and waist circumference (WC) (n=564), blood pressure (BP) (n=537) and biomarkers (minimum n=206). Generalised linear mixed models estimated the interactive effects of the PA and SB interventions on the outcomes. If there was no interaction, the main effects were assessed. RESULTS: At 18 months, there were intervention effects on children's weekday SB (-27 min, 95% CI: -47.3 to -5.3) for the PA intervention, and on children's average day PA (5.5 min, 95% CI: 0.1 to 10.8) for the SB intervention. At 30 months, there was an intervention effect for children's average day SB (-33.3 min, 95% CI: -50.6 and -16.0) for the SB intervention. Children's BMI (PA and SB groups) and systolic BP (combined group) were lower, and diastolic BP (PA group) was higher. There were positive effects on WC at both time points (SB intervention) and mixed effects on blood parameters. CONCLUSIONS: The Transform-Us! PA and SB interventions show promise as a pragmatic approach for reducing children's SB and adiposity indicators; but achieving substantial increases in PA remains challenging. TRIAL REGISTRATION: ISRCTN83725066; ACTRN12609000715279.

Do neighbourhood traffic-related air pollution and socio-economic status moderate the associations of the neighbourhood physical environment with cognitive function? Findings from the AusDiab study.

Characteristics of the neighbourhood environment, including the built and natural environment, area-level socio-economic status (SES) and air pollution, have been linked to cognitive health. However, most studies have focused on single neighbourhood characteristics and have not considered the extent to which the effects of environmental factors may interact. We examined the associations of measures of the neighbourhood built and natural environment, area-level SES and traffic-related air pollution (TRAP) with two cognitive function domains (memory and processing speed), and the extent to which area-level SES and TRAP moderated the associations. We used cross-sectional data from the AusDiab3 study, an Australian cohort study of adults (mean age: 61 years) in 2011-12 (N = 4141) for which geocoded residential addresses were available. Spatial data were used to create composite indices of built environment complexity (population density, intersection density, non-commercial land use mix, commercial land use) and natural environment (parkland and blue spaces). Area-level SES was obtained from national census indices and TRAP was based on estimates of annual average levels of nitrogen dioxide (NO2). Confounder-adjusted generalised additive mixed models were used to estimate the independent associations of the environmental measures with cognitive function and the moderating effects of area-level SES and TRAP. The positive associations between built environment complexity and memory were stronger in those living in areas with higher SES and lower NO2 concentrations. A positive association between the natural environment and memory was found only in those living in areas with lower NO2 concentrations and average or below-average SES. Built environment complexity and the natural environment were positively related to processing speed. Complex urban environments and access to nature may benefit cognitive health in ageing populations. For higher-order cognitive abilities, such as memory, these positive effects may be stronger in areas with lower levels of TRAP.

Lifestyle factors as mediators of area-level socio-economic differentials in cardiovascular disease risk factors. The Tromsø Study.

Introduction: Cardiovascular disease (CVD) is a leading cause of death and disability and living in areas with low socio-economic status (SES) is associated with increased risk of CVD. Lifestyle factors such as smoking, physical inactivity, an unhealthy diet and harmful alcohol use are main risk factors that contribute to other modifiable risk factors, such as hypertension, raised blood cholesterol, obesity, and diabetes. The potential impact of area-level socio-economic status (ASES) on metabolic CVD risk factors via lifestyle behaviors independent of individual SES has not been investigated previously. Aims: To estimate associations of ASES with CVD risk factors and the mediating role of lifestyle behaviors independent of individual-level SES. Methods: In this cross-sectional study, we included 19,415 participants (52% women) from the seventh survey of the Tromsø Study (2015-2016) (Tromsø7). The exposure variable ASES was created by aggregating individual-level SES variables (education, income, housing ownership) at the geographical subdivision level. Individual-level SES data and geographical subdivision of Tromsø municipality (36 areas) were obtained from Statistics Norway. Variables from questionnaires and clinical examinations obtained from Tromsø7 were used as mediators (smoking, snuff, alcohol, and physical activity), while the outcome variables were body mass index (BMI), total/high-density lipoprotein (HDL) cholesterol ratio, waist circumference, hypertension, diabetes. Mediation and mediated moderation analysis were performed with age as a moderator, stratified by sex. Results: ASES was significantly associated with all outcome variables. CVD risk factor level declined with an increase in ASES. These associations were mediated by differences in smoking habits, alcohol use and physical activity. The associations of ASES with total/HDL cholesterol ratio and waist circumference (women) were moderated by age, and the moderating effects were mediated by smoking and physical activity in both sexes. The largest mediated effects were seen in the associations of ASES with total/HDL cholesterol ratio, with the mediators accounting for 43% of the observed effects. Conclusions: Living in lower SES areas is associated with increased CVD risk due to unhealthy lifestyle behaviors, such as smoking, alcohol use and physical inactivity. These associations were stronger in women and among older participants.

Machine Learning for Prediction of Cognitive Health in Adults Using Sociodemographic, Neighbourhood Environmental, and Lifestyle Factors.

The environment we live in, and our lifestyle within this environment, can shape our cognitive health. We investigated whether sociodemographic, neighbourhood environment, and lifestyle variables can be used to predict cognitive health status in adults. Cross-sectional data from the AusDiab3 study, an Australian cohort study of adults (34-97 years) (n = 4141) was used. Cognitive function was measured using processing speed and memory tests, which were categorized into distinct classes using latent profile analysis. Sociodemographic variables, measures of the built and natural environment estimated using geographic information system data, and physical activity and sedentary behaviours were used as predictors. Machine learning was performed using gradient boosting machine, support vector machine, artificial neural network, and linear models. Sociodemographic variables predicted processing speed (r2 = 0.43) and memory (r2 = 0.20) with good accuracy. Lifestyle factors also accurately predicted processing speed (r2 = 0.29) but weakly predicted memory (r2 = 0.10). Neighbourhood and built environment factors were weak predictors of cognitive function. Sociodemographic (AUC = 0.84) and lifestyle (AUC = 0.78) factors also accurately classified cognitive classes. Sociodemographic and lifestyle variables can predict cognitive function in adults. Machine learning tools are useful for population-level assessment of cognitive health status via readily available and easy-to-collect data.

Is level of implementation linked with intervention outcomes? Process evaluation of the TransformUs intervention to increase children's physical activity and reduce sedentary behaviour.

BACKGROUND: TransformUs was a four-arm school-based intervention to increase physical activity and reduce sedentary behaviour among primary school children. Pedagogical and environmental strategies targeted the classroom, school grounds and family setting. The aims of this study were to evaluate program fidelity, dose, appropriateness, satisfaction and sustainability, and associations between implementation level and outcomes among the three intervention arms. METHODS: At baseline, 18-months (mid-intervention) and 30-months (post-intervention), teachers, parents and children completed surveys, and children wore GT3X ActiGraph accelerometers for 8 days at each time point to determine physical activity and sedentary time. Implementation data were pooled across the three intervention groups and teachers were categorised by level of implementation: (i) 'Low' (< 33% delivered); (ii) 'Moderate' (33-67% delivered); and (iii) 'High' (> 67% delivered). Linear and logistic mixed models examined between group differences in implementation, and the association with children's physical activity and sedentary time outcomes. Qualitative survey data were analysed thematically. RESULTS: Among intervention recipients, 52% (n = 85) of teachers, 29% (n = 331) of parents and 92% (n = 407) of children completed baseline evaluation surveys. At 18-months, teachers delivered on average 70% of the key messages, 65% set active/standing homework, 30% reported delivering > 1 standing lesson/day, and 56% delivered active breaks per day. The majority of teachers (96%) made activity/sports equipment available during recess and lunch, and also used this equipment in class (81%). Fidelity and dose of key messages and active homework reduced over time, whilst fidelity of standing lessons, active breaks and equipment use increased. TransformUs was deemed appropriate for the school setting and positively received. Implementation level and child behavioural outcomes were not associated. Integration of TransformUs into existing practices, children's enjoyment, and teachers' awareness of program benefits all facilitated delivery and sustainability. CONCLUSIONS: This study demonstrated that intervention dose and fidelity increased over time, and that children's enjoyment, senior school leadership and effective integration of interventions into school practices facilitated improved intervention delivery and sustainability. Teacher implementation level and child behavioural outcomes were unrelated, suggesting intervention efficacy was achieved irrespective of implementation variability. The potential translatability of TransformUs into practice contexts may therefore be increased. Findings have informed scale-up of TransformUs across Victoria, Australia. TRIAL REGISTRATION: International Standard Randomized Controlled Trial Number ISRCTN83725066; Australian New Zealand Clinical Trials Registry Number ACTRN12609000715279. Registered 19 August 2009. Available at: https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=308387&isReview=true.

The neighbourhood environment and profiles of the metabolic syndrome.

BACKGROUND: There is a dearth of studies on how neighbourhood environmental attributes relate to the metabolic syndrome (MetS) and profiles of MetS components. We examined the associations of interrelated aspects of the neighbourhood environment, including air pollution, with MetS status and profiles of MetS components. METHODS: We used socio-demographic and MetS-related data from 3681 urban adults who participated in the 3rd wave of the Australian Diabetes, Obesity and Lifestyle Study. Neighbourhood environmental attributes included area socio-economic status (SES), population density, street intersection density, non-commercial land use mix, percentages of commercial land, parkland and blue space. Annual average concentrations of NO2 and PM2.5 were estimated using satellite-based land-use regression models. Latent class analysis (LCA) identified homogenous groups (latent classes) of participants based on MetS components data. Participants were then classified into five metabolic profiles according to their MetS-components latent class and MetS status. Generalised additive mixed models were used to estimate relationships of environmental attributes with MetS status and metabolic profiles. RESULTS: LCA yielded three latent classes, one including only participants without MetS ("Lower probability of MetS components" profile). The other two classes/profiles, consisting of participants with and without MetS, were "Medium-to-high probability of high fasting blood glucose, waist circumference and blood pressure" and "Higher probability of MetS components". Area SES was the only significant predictor of MetS status: participants from high SES areas were less likely to have MetS. Area SES, percentage of commercial land and NO2 were associated with the odds of membership to healthier metabolic profiles without MetS, while annual average concentration of PM2.5 was associated with unhealthier metabolic profiles with MetS. CONCLUSIONS: This study supports the utility of operationalising MetS as a combination of latent classes of MetS components and MetS status in studies of environmental correlates. Higher socio-economic advantage, good access to commercial services and low air pollution levels appear to independently contribute to different facets of metabolic health. Future research needs to consider conducting longitudinal studies using fine-grained environmental measures that more accurately characterise the neighbourhood environment in relation to behaviours or other mechanisms related to MetS and its components.

From motorised to active travel: using GPS data to explore potential physical activity gains among adolescents.

BACKGROUND: A high proportion of adolescents worldwide are not doing enough physical activity for health benefits. Replacing short motorised trips with walking or cycling has the potential to increase physical activity at the population level. This study aimed to estimate the proportion of short distance motorised trips that could be replaced with walking or cycling, and the potential physical activity gains by sociodemographic and trip characteristics. METHODS: Data were from a subsample of the NEighbourhood Activity in Youth (NEArbY) study conducted among adolescents in Melbourne. A total of 217 adolescents with at least one motorised trip completed a survey and wore a Global Positioning Systems (GPS) device for eight consecutive days. Classification of travel modes were based on speed. GPS data points were geocoded in ArcGIS. Motorised trips within walkable (1.3 km) and cyclable (4.2 km) distances were identified (threshold based on 80th percentile of walking and cycling trip distances among Victorian adolescents), and the additional physical activity minutes that could be accrued by replacing walkable or cyclable motorised trip to active trips were quantified. Multilevel linear regression was used to assess differences in physical activity minutes gain by sociodemographic and trip characteristics. RESULTS: A total of 4,116 motorised trips were made. Of these, 17% were walkable and 61% were cyclable. Replacing motorised trips by walking and cycling resulted in estimated gains of six minutes and 15 min of physical activity per day, respectively. CONCLUSION: The sizable proportion of replaceable trips and potential physical activity gains from this shift calls for attention to improve safe and connected infrastructure to support active travel.

Older People's Usage Pattern, Satisfaction with Community Facility and Well-Being in Urban Old Districts.

Community facilities are an important element that supports older people's daily life and promotes their well-being. However, there is a dearth of comprehensive studies on the effect of planning and design of different types of community facilities on older people's usage patterns and satisfaction. This study aims to provide a framework to explore the relationship among the planning of community facilities, older people's usage and satisfaction level and well-being for different types of community facilities. Both spatial analysis and questionnaire survey (n = 497) methods are employed in this study. This study finds that commercial (89.34%), municipal (83.10%) and leisure (88.13%) facilities are most commonly used by older people. This study suggests that older people's frequency of visiting community facilities is mainly affected by the purpose of visiting a community facility. Planning and design quality of the community facility are found to be significantly associated with older people's satisfaction level with using a community facility. In addition, older people's higher satisfaction level and usage level of community facilities could increase their physical and psychological well-being. The findings of this study not only contribute to the knowledge gap of older people's usage and satisfaction with using community facilities but also suggest that planners should aim toward a better distribution of community facilities to improve older adults' well-being.