Neighbourhood environments and cognitive health in the longitudinal Personality and Total Health (PATH) through life study: A 12-year follow-up of older Australians

Background: Urban neighbourhood environments may impact older adults’ cognitive health. However, longitudinal studies examining key environmental correlates of cognitive health are lacking. We estimated cross-sectional and longitudinal associations of neighbourhood built and natural environments and ambient air pollution with multiple cognitive health outcomes in Australian urban dwellers aged 60+ years. Methods: The study included 1160 participants of the PATH Through Life study (60+ cohort) who were followed up for 12 years (four assessments; 2001/02 to 2013/15) and with data on socio-demographics, health, cognitive functions and diagnoses, and full residential address. Neighbourhood environmental features encompassed population and street-intersection densities, non-commercial land use mix, transit points, presence of blue space, percentages of commercial land, parkland and tree cover, and annual average PM2.5 and NO2 concentrations. All exposures except for tree cover were assessed at two time points. Generalised additive mixed models estimated associations of person-level average, and within-person changes in, exposures with cognitive functions. Multi-state hidden Markov models estimated the associations of neighbourhood attributes with transitions to/from mild cognitive impairment (MCI). Results: Dense, destination-rich neighbourhoods were associated with a lower likelihood of transition to MCI and reversal to no MCI. Positive cross-sectional and longitudinal associations of non-commercial land use mix, street intersection density and percentage of commercial land were observed especially with global cognition and processing speed. While access to parkland and blue spaces were associated with a lower risk of transition to MCI, the findings related to cognitive functions were mixed and supportive of an effect of parkland on verbal memory only. Higher levels of PM2.5 and NO2 were consistently associated with steeper declines and/or decreases in cognitive functions and worse cognitive states across time. Conclusion: To support cognitive health in ageing populations, neighbourhoods need to provide an optimal mix of environmental complexity, destinations and access to the natural environment and, at the same time, minimise ambient air pollution

Measuring Coverage in MNCH:A Prospective Validation Study in Pakistan and Bangladesh on Measuring Correct Treatment of Childhood Pneumonia

Antibiotic treatment for pneumonia as measured by Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys (MICS) is a key indicator for tracking progress in achieving Millennium Development Goal 4. Concerns about the validity of this indicator led us to perform an evaluation in urban and rural settings in Pakistan and Bangladesh.Caregivers of 950 children under 5 y with pneumonia and 980 with "no pneumonia" were identified in urban and rural settings and allocated for DHS/MICS questions 2 or 4 wk later. Study physicians assigned a diagnosis of pneumonia as reference standard; the predictive ability of DHS/MICS questions and additional measurement tools to identify pneumonia versus non-pneumonia cases was evaluated. Results at both sites showed suboptimal discriminative power, with no difference between 2- or 4-wk recall. Individual patterns of sensitivity and specificity varied substantially across study sites (sensitivity 66.9% and 45.5%, and specificity 68.8% and 69.5%, for DHS in Pakistan and Bangladesh, respectively). Prescribed antibiotics for pneumonia were correctly recalled by about two-thirds of caregivers using DHS questions, increasing to 72% and 82% in Pakistan and Bangladesh, respectively, using a drug chart and detailed enquiry.Monitoring antibiotic treatment of pneumonia is essential for national and global programs. Current (DHS/MICS questions) and proposed new (video and pneumonia score) methods of identifying pneumonia based on maternal recall discriminate poorly between pneumonia and children with cough. Furthermore, these methods have a low yield to identify children who have true pneumonia. Reported antibiotic treatment rates among these children are therefore not a valid proxy indicator of pneumonia treatment rates. These results have important implications for program monitoring and suggest that data in its current format from DHS/MICS surveys should not be used for the purpose of monitoring antibiotic treatment rates in children with pneumonia at the present time

A single risk assessment for the most common diseases of ageing, developed and validated on 10 cohort studies

BackgroundWe aimed to develop risk tools for dementia, stroke, myocardial infarction (MI), and diabetes, for adults aged ≥ 65 years using shared risk factors.MethodsData were obtained from 10 population-based cohorts (N = 41,755) with median follow-up time (years) for dementia, stroke, MI, and diabetes of 6.2, 7.0, 6.8, and 7.4, respectively. Disease-free participants at baseline were included, and 22 risk factors (sociodemographic, medical, lifestyle, laboratory biomarkers) were evaluated. Two risk tools (DemNCD and DemNCD-LR based on Fine and Gray sub-distribution and logistic regression [LR], respectively) were developed and validated. Predictive accuracies of these risk tools were assessed using Harrel’s C-statistics and area under the curve (AUC) and 95% confidence interval (CI). Model calibration was conducted using Hosmer–Lemeshow goodness of fit test along calibration plots.ResultsBoth the DemNCD and DemNCD-LR resulted in similar predictive accuracy for each outcome. The overall AUC (95% CI) for dementia, stroke, MI, and diabetes risk tool were 0·68 (0·65, 0·70), 0·58 (0·54, 0·61), 0·65 (0·61, 0·68), and 0·68 (0·64, 0·72), respectively, for males. For females, these figures were 0·65 (0·63, 0·67), 0·55 (0·52, 0·57), 0·65 (0·62, 0·68), and 0·61 (0·57, 0·65).ConclusionsThe DemNCD is the first tool to predict both dementia and multiple cardio-metabolic diseases using comprehensive risk factors and provided similar predictive accuracy to existing risk tools. It has similar predictive accuracy as tools designed for single outcomes in this age-group. DemNCD has the potential to be used in community and clinical settings as it includes self-reported and routinely available clinical measures

The use of driver screening tools to predict self-reported crashes and incidents in older drivers

There is a clear need to identify older drivers at increased crash risk, without additional burden on the individual or licensing system. Brief off-road screening tools have been used to identify unsafe drivers and drivers at risk of losing their license. The aim of the current study was to evaluate and compare driver screening tools in predicting prospective self-reported crashes and incidents over 24 months in drivers aged 60 years and older. 525 drivers aged 63–96 years participated in the prospective Driving Aging Safety and Health (DASH) study, completing an on-road driving assessment and seven off-road screening tools (Multi-D battery, Useful Field of View, 14-Item Road Law, Drive Safe, Drive Safe Intersection, Maze Test, Hazard Perception Test (HPT)), along with monthly self-report diaries on crashes and incidents over a 24-month period. Over the 24 months, 22% of older drivers reported at least one crash, while 42% reported at least one significant incident (e.g., near miss). As expected, passing the on-road driving assessment was associated with a 55% [IRR 0.45, 95% CI 0.29–0.71] reduction in self-reported crashes adjusting for exposure (crash rate), but was not associated with reduced rate of a significant incident. For the off-road screening tools, poorer performance on the Multi-D test battery was associated with a 22% [IRR 1.22, 95% CI 1.08–1.37] increase in crash rate over 24 months. Meanwhile, all other off-road screening tools were not predictive of rates of crashes or incidents reported prospectively. The finding that only the Multi-D battery was predictive of increased crash rate, highlights the importance of accounting for age-related changes in vision, sensorimotor skills and cognition, as well as driving exposure, in older drivers when using off-road screening tools to assess future crash risk

Study protocol for development and validation of a single tool to assess risks of stroke, diabetes mellitus, myocardial infarction and dementia: DemNCD-Risk

Introduction Current efforts to reduce dementia focus on prevention and risk reduction by targeting modifiable risk factors. As dementia and cardiometabolic non-communicable diseases (NCDs) share risk factors, a single risk-estimating tool for dementia and multiple NCDs could be cost-effective and facilitate concurrent assessments as compared with a conventional single approach. The aim of this study is to develop and validate a new risk tool that estimates an individual's risk of developing dementia and other NCDs including diabetes mellitus, stroke and myocardial infarction. Once validated, it could be used by the public and general practitioners. Methods and analysis Ten high-quality cohort studies from multiple countries were identified, which met eligibility criteria, including large representative samples, long-term follow-up, data on clinical diagnoses of dementia and NCDs, recognised modifiable risk factors for the four NCDs and mortality data. Pooled harmonised data from the cohorts will be used, with 65% randomly allocated for development of the predictive model and 35% for testing. Predictors include sociodemographic characteristics, general health risk factors and lifestyle/behavioural risk factors. A subdistribution hazard model will assess the risk factors' contribution to the outcome, adjusting for competing mortality risks. Point-based scoring algorithms will be built using predictor weights, internally validated and the discriminative ability and calibration of the model will be assessed for the outcomes. Sensitivity analyses will include recalculating risk scores using logistic regression. Ethics and dissemination Ethics approval is provided by the University of New South Wales Human Research Ethics Committee (UNSW HREC; protocol numbers HC200515, HC3413). All data are deidentified and securely stored on servers at Neuroscience Research Australia. Study findings will be presented at conferences and published in peer-reviewed journals. The tool will be accessible as a public health resource. Knowledge translation and implementation work will explore strategies to apply the tool in clinical practice

Baseline characteristics of the study children.

<p>Data are given as number (percent) unless otherwise indicated.</p>a<p>There was only one child in the 0–2 age group at the Bangladesh rural site, hence a standard deviation value could not be calculated.</p><p>SD, standard deviation.</p

Bangladesh rural site—flowchart of selection of pneumonia and no-pneumonia cases in the rural setting.

<p>Bangladesh rural site—flowchart of selection of pneumonia and no-pneumonia cases in the rural setting.</p

Discriminative power of DHS/MICS questions about suspected pneumonia and of video for identifying childhood pneumonia (based on 2-wk and 4-wk recall).

<p>Discriminative power of DHS/MICS questions about suspected pneumonia and of video for identifying childhood pneumonia (based on 2-wk and 4-wk recall).</p