Sex differences in late-life memory decline may be explained by sex differences in dementia risk factors. Episodic memory and dementia risk factors were assessed in young, middle-aged and older ...adults over 12 years in a population-based sample (N = 7485). For men in midlife and old age, physical, cognitive and social activities were associated with less memory decline, and financial hardship was associated with more. APOE e4 and vascular risk factors were associated with memory decline for women in midlife. Depression, cognitive and physical activity were associated with memory change in older women. Incident midlife hypertension (β = - 0.48, 95% CI - 0.87, - 0.09, p = 0.02) was associated with greater memory decline in women and incident late-life stroke accounted for greater memory decline in men (β = - 0.56, 95% CI - 1.12, - 0.01), p = 0.05). Women have fewer modifiable risk factors than men. Stroke and hypertension explained sex differences in memory decline for men and women respectively.
Multiple imputation (MI) is now widely used to handle missing data in longitudinal studies. Several MI techniques have been proposed to impute incomplete longitudinal covariates, including standard ...fully conditional specification (FCS-Standard) and joint multivariate normal imputation (JM-MVN), which treat repeated measurements as distinct variables, and various extensions based on generalized linear mixed models. Although these MI approaches have been implemented in various software packages, there has not been a comprehensive evaluation of the relative performance of these methods in the context of longitudinal data.
Using both empirical data and a simulation study based on data from the six waves of the Longitudinal Study of Australian Children (N = 4661), we investigated the performance of a wide range of MI methods available in standard software packages for investigating the association between child body mass index (BMI) and quality of life using both a linear regression and a linear mixed-effects model.
In this paper, we have identified and compared 12 different MI methods for imputing missing data in longitudinal studies. Analysis of simulated data under missing at random (MAR) mechanisms showed that the generally available MI methods provided less biased estimates with better coverage for the linear regression model and around half of these methods performed well for the estimation of regression parameters for a linear mixed model with random intercept. With the observed data, we observed an inverse association between child BMI and quality of life, with available data as well as multiple imputation.
Both FCS-Standard and JM-MVN performed well for the estimation of regression parameters in both analysis models. More complex methods that explicitly reflect the longitudinal structure for these analysis models may only be needed in specific circumstances such as irregularly spaced data.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
We assessed the association between the duration of diarrhoea and the risk ofpneumonia incidence among children <5 years of age.
We analysed data from a cluster randomized controlled trial in ...Karachi, Pakistan, which assessed the effect of promoting hand washing with soap (antibacterial and plain) on child health. Field workers visited households with children <5 years of age weekly and asked primary caregivers if their child had diarrhoea, cough or difficulty breathing in the preceding week. We used the WHO clinical case definitions for diarrhoea and pneumonia.We used adjusted time-to-event analyses with cumulative diarrhoea prevalence over the previous 2 and 4 weeks as exposure and pneumonia as outcome. We calculated the attributable risk of pneumonia due to recent diarrhoea across the intervention groups.
873 households with children <5 years were visited. Children had an increased risk of pneumonia for every additional day of diarrhoea in the 2 weeks (1.06, 95% CI: 1.03-1.09) and 4 weeks (1.04, 95% CI: 1.03-1.06) prior to the week of pneumonia onset. The attributable risk of pneumonia cases due to recent exposure to diarrhoea was 6%. A lower associated pneumonia risk following diarrhoea was found in the control group: (3%) compared with soap groups (6% in antibacterial soap, 9% in plain soap).
Children <5 years of age are at an increased risk of pneumonia following recent diarrhoeal illness. Public health programmes that prevent diarrhoea may also reduce the burden of respiratory illnesses.
Giardiasis is a common diarrhoeal disease caused by the protozoan Giardia duodenalis. It is prevalent in low-income countries in the context of inadequate access to water, sanitation and hygiene ...(WASH), and is frequently co-endemic with neglected tropical diseases such as soil-transmitted helminth (STH) infections. Large-scale periodic deworming programmes are often implemented in these settings; however, there is limited evidence for the impact of regular anthelminthic treatment on G. duodenalis infection. Additionally, few studies have examined the impact of WASH interventions on G. duodenalis.
The WASH for WORMS cluster randomised controlled trial was conducted in remote communities in Manufahi municipality, Timor-Leste, between 2012 and 2016. All study communities received four rounds of deworming with albendazole at six-monthly intervals. Half were randomised to additionally receive a community-level WASH intervention following study baseline. We measured G. duodenalis infection in study participants every six months for two years, immediately prior to deworming, as a pre-specified secondary outcome of the trial. WASH access and behaviours were measured using questionnaires.
There was no significant change in G. duodenalis prevalence in either study arm between baseline and the final study follow-up. We found no additional benefit of the community-level WASH intervention on G. duodenalis infection (relative risk: 1.05, 95% CI: 0.72-1.54). Risk factors for G. duodenalis infection included living in a household with a child under five years of age (adjusted odds ratio, aOR: 1.35, 95% CI: 1.04-1.75), living in a household with more than six people (aOR: 1.32, 95% CI: 1.02-1.72), and sampling during the rainy season (aOR: 1.23, 95% CI: 1.04-1.45). Individuals infected with the hookworm Necator americanus were less likely to have G. duodenalis infection (aOR: 0.71, 95% CI: 0.57-0.88).
Prevalence of G. duodenalis was not affected by a community WASH intervention or by two years of regular deworming with albendazole. Direct household contacts appear to play a dominant role in driving transmission. We found evidence of antagonistic effects between G. duodenalis and hookworm infection, which warrants further investigation in the context of global deworming efforts. Trial registration Australian New Zealand Clinical Trials Registry, ACTRN12614000680662. Registered 27 June 2014, retrospectively registered. https://anzctr.org.au/Trial/Registration/TrialReview.aspx?id=366540 .
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.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Habits play an important role in physical activity (PA) engagement; however, these associations in older people are not well understood. The present study aimed to investigate the relationship ...between engagement in types of PA and their automaticity in older people, using an observational, cross-sectional design. Current hours engaged in planned exercise (excluding walking), planned walking, and incidental activities and the automaticity of those PA behaviors were measured in 127 community-dwelling Australians aged 65 years and older via an online questionnaire. After controlling for demographic and health factors (age, gender, education level, body mass index, history of falls, and anxiety and depression symptoms), higher automaticity scores were associated with more hours undertaking planned walking and incidental activity but not planned exercise. Although preliminary, these findings indicate that the role of habit in maintaining PA in older people may, therefore, differ depending on the type of activity.
Abstract
Estimating the fraction of dementia cases in a population attributable to a risk factor or combination of risk factors (the population attributable fraction (PAF)) informs the design and ...choice of dementia risk-reduction activities. It is directly relevant to dementia prevention policy and practice. Current methods employed widely in the dementia literature to combine PAFs for multiple dementia risk factors assume a multiplicative relationship between factors and rely on subjective criteria to develop weightings for risk factors. In this paper we present an alternative approach to calculating the PAF based on sums of individual risk. It incorporates individual risk factor interrelationships and enables a range of assumptions about the way in which multiple risk factors will combine to affect dementia risk. Applying this method to global data demonstrates that the previous estimate of 40% is potentially too conservative an estimate of modifiable dementia risk and would necessitate subadditive interaction between risk factors. We calculate a plausible conservative estimate of 55.7% (95% confidence interval: 55.2, 56.1) based on additive risk factor interaction.
IntroductionDigital health interventions are cost-effective and easily accessible, but there is currently a lack of effective online options for dementia prevention especially for people at risk due ...to mild cognitive impairment (MCI) or subjective cognitive decline (SCD).Methods and analysisMyCOACH (COnnected Advice for Cognitive Health) is a tailored online dementia risk reduction programme for adults aged ≥65 living with MCI or SCD. The MyCOACH trial aims to evaluate the programme’s effectiveness in reducing dementia risk compared with an active control over a 64-week period (N=326). Eligible participants are randomly allocated to one of two intervention arms for 12 weeks: (1) the MyCOACH intervention programme or (2) email bulletins with general healthy ageing information (active control). The MyCOACH intervention programme provides participants with information about memory impairments and dementia, memory strategies and different lifestyle factors associated with brain ageing as well as practical support including goal setting, motivational interviewing, brain training, dietary and exercise consultations, and a 26-week post-intervention booster session. Follow-up assessments are conducted for all participants at 13, 39 and 65 weeks from baseline, with the primary outcome being exposure to dementia risk factors measured using the Australian National University-Alzheimer’s Disease Risk Index. Secondary measures include cognitive function, quality of life, functional impairment, motivation to change behaviour, self-efficacy, morale and dementia literacy.Ethics and disseminationEthical approval was obtained from the University of New South Wales Human Research Ethics Committee (HC210012, 19 February 2021). The results of the study will be disseminated in peer-reviewed journals and research conferences.Trial registration numberACTRN12621000977875.
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.
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 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.
Traditional longitudinal aging research involves studying the same individuals over a long period, with measurement intervals typically several years apart. App-based studies have the potential to ...provide new insights into life-course aging by improving the accessibility, temporal specificity, and real-world integration of data collection. We developed a new research app for iOS named Labs Without Walls to facilitate the study of life-course aging. Combined with data collected using paired smartwatches, the app collects complex data including data from one-time surveys, daily diary surveys, repeated game-like cognitive and sensory tasks, and passive health and environmental data.
The aim of this protocol is to describe the research design and methods of the Labs Without Walls study conducted between 2021 and 2023 in Australia.
Overall, 240 Australian adults will be recruited, stratified by age group (18-25, 26-35, 36-45, 46-55, 56-65, 66-75, and 76-85 years) and sex at birth (male and female). Recruitment procedures include emails to university and community networks, as well as paid and unpaid social media advertisements. Participants will be invited to complete the study onboarding either in person or remotely. Participants who select face-to-face onboarding (n=approximately 40) will be invited to complete traditional in-person cognitive and sensory assessments to be cross-validated against their app-based counterparts. Participants will be sent an Apple Watch and headphones for use during the study period. Participants will provide informed consent within the app and then begin an 8-week study protocol, which includes scheduled surveys, cognitive and sensory tasks, and passive data collection using the app and a paired watch. At the conclusion of the study period, participants will be invited to rate the acceptability and usability of the study app and watch. We hypothesize that participants will be able to successfully provide e-consent, input survey data through the Labs Without Walls app, and have passive data collected over 8 weeks; participants will rate the app and watch as user-friendly and acceptable; the app will allow for the study of daily variability in self-perceptions of age and gender; and data will allow for the cross-validation of app- and laboratory-based cognitive and sensory tasks.
Recruitment began in May 2021, and data collection was completed in February 2023. The publication of preliminary results is anticipated in 2023.
This study will provide evidence regarding the acceptability and usability of the research app and paired watch for studying life-course aging processes on multiple timescales. The feedback obtained will be used to improve future iterations of the app, explore preliminary evidence for intraindividual variability in self-perceptions of aging and gender expression across the life span, and explore the associations between performance on app-based cognitive and sensory tests and that on similar traditional cognitive and sensory tests.
DERR1-10.2196/47053.
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