'First of all, I need training': a qualitative study evaluating the Fiji community health worker training program.

BACKGROUND: Fiji faces a growing burden of diseases and a significant emigration of health workers, heightening the role of community health workers (CHWs) in healthcare delivery. Effective training is crucial for CHWs to enhance their capacity and service quality. This study evaluates CHW training in Fiji, aiming to identify areas for improvement. METHODS: A qualitative study was conducted, encompassing a review of national policies on CHW training, six focus group discussions, and interviews with CHWs and their supervisors across Fijian subdivisions. This study was collaboratively designed with Fiji's Ministry of Health and Medical Services (MOHMS). Data was transcribed, coded, and thematically analysed using the Community Health Workers Assessment and Improvement Matrix (CHW-AIM). FINDINGS: While CHW training policies in Fiji are well-established, discrepancies exist between the policy and its implementation. Challenges include inconsistent training for new recruits, limited resources, and variability in training content and frequency of training across divisions, especially concerning noncommunicable disease (NCD) training. INTERPRETATION: To enhance the CHW training program in Fiji, a restructuring and standardisation of both pre-service and in-service training is necessary, tailored to the needs of each division. Investment in ongoing capacity building, alongside the development and revision of training guidelines, particularly for managing NCD complications in the community, is crucial. Implementing these changes will enable CHWs in Fiji to be better equipped for providing essential community-based care.

"We're on the ground, we know what needs to be done": Exploring the role of Aboriginal Health Workers in primary health care.

Background: Aboriginal Health Workers (AHWs) are core providers of primary health care (PHC) for First Nations peoples in Australia. However, the national AHW workforce is aging and in short supply. There is a poor understanding of the factors contributing to this attrition from the perspectives of AHWs themselves. This study aimed to systematically explore the current functioning and sustainability of AHWs in NSW PHC by amplifying AHW voices. Materials and methods: This study was co-designed with three Aboriginal health services in NSW. It included a literature review exploring the role of AHWs in NSW, and yarns with AHWs and their supervisors at participating services. Yarning is an Indigenous approach to knowledge generation centered upon storytelling. The yarns were guided by the USAID-developed Community Health Worker Assessment and Improvement Matrix. Yarn transcripts were analyzed using cyclical thematic analysis to identify key facilitators and challenges for AHW practice. Results: The yarns highlighted five categories of change that are required to ensure AHW sustainability: community connection, recognition, value, support, and an inclusive health system. The yarns revealed that there are both service- and system-level factors influencing each of these categories of change. Conclusions: The lived experiences of AHWs in NSW emphasize five key categories of change that are required to ensure workforce sustainability. It is evident that a system-wide paradigm shift to better include holistic approaches to health is necessary to truly ensure sustainability. Co-designing similar studies with ACCHOs across NSW can help inform this change.

Why do strategies to strengthen primary health care succeed in some places and fail in others? Exploring local variation in the effectiveness of a community health worker managed digital health intervention in rural India.

INTRODUCTION: Digital health interventions (DHIs) have huge potential as support modalities to identify and manage cardiovascular disease (CVD) risk in resource-constrained settings, but studies assessing them show modest effects. This study aims to identify variation in outcomes and implementation of SMARTHealth India, a cluster randomised trial of an ASHA-managed digitally enabled primary healthcare (PHC) service strengthening strategy for CVD risk management, and to explain how and in what contexts the intervention was effective. METHODS: We analysed trial outcome and implementation data for 18 PHC centres and collected qualitative data via focus groups with ASHAs (n=14) and interviews with ASHAs, PHC facility doctors and fieldteam mangers (n=12) Drawing on principles of realist evaluation and an explanatory mixed-methods design we developed mechanism-based explanations for observed outcomes. RESULTS: There was substantial between-cluster variation in the primary outcome (overall: I2=62.4%, p<=0.001). The observed heterogeneity in trial outcomes was not attributable to any single factor. Key mechanisms for intervention effectiveness were community trust and acceptability of doctors' and ASHAs' new roles, and risk awareness. Enabling local contexts were seen to evolve over time and in response to the intervention. These included obtaining legitimacy for ASHAs' new roles from trusted providers of curative care; ASHAs' connections to community and to qualified providers; their responsiveness to community needs; and the accessibility, quality and appropriateness of care provided by higher level medical providers, including those outside of the implementing (public) subsystem. CONCLUSION: Local contextual factors were significant influences on the effectiveness of this DHI-enabled PHC service strategy intervention. Local adaptions need to be planned for, monitored and responded to over time. By identifying plausible explanations for variation in outcomes between clusters, we identify potential strategies to strengthen such interventions.

A computer-guided quality improvement tool for primary health care: cost-effectiveness analysis based on TORPEDO trial data.

OBJECTIVE: To assess the cost-effectiveness of a computer-guided quality improvement intervention for primary health care management of cardiovascular disease (CVD) in people at high risk. DESIGN: Modelled cost-effectiveness analysis of the HealthTracker intervention and usual care for people with high CVD risk, based on TORPEDO trial data on prescribing patterns, changes in intermediate risk factors (low-density lipoprotein cholesterol, systolic blood pressure), and Framingham risk scores. PARTICIPANTS: Hypothetical population of people with high CVD risk attending primary health care services in a New South Wales primary health network (PHN) of mean size. INTERVENTION: HealthTracker, integrated into health care provider electronic health record systems, provides real time decision support, risk communication, a clinical audit tool, and a web portal for performance feedback. MAIN OUTCOME MEASURES: Incremental cost-effectiveness ratios (ICERs): difference in costs of the intervention and usual care divided by number of CVD events averted with HealthTracker. RESULTS: The estimated numbers of major CVD events over five years per 1000 patients at high CVD risk were lower in PHNs using HealthTracker, both for patients with prior CVD events (secondary prevention; 259 v 267 with usual care) and for those without prior events (primary prevention; 168 v 176). Medication costs were higher and hospitalisation costs lower with HealthTracker than with usual care for both primary and secondary prevention. The estimated ICER for one averted CVD event was $7406 for primary prevention and $17 988 for secondary prevention. CONCLUSION: Modelled cost-effectiveness analyses provide information that can assist decisions about investing in health care quality improvement interventions. We estimate that HealthTracker could prevent major CVD events for less than $20 000 per event averted. TRIAL REGISTRATION (TORPEDO): Australian New Zealand Clinical Trials Registry, ACTRN 12611000478910.

Discussions about evidence and preferences in real-life general practice consultations with older patients.

OBJECTIVES: To explore how decisions are made in real-life general practice consultations with older patients (65+ years), and examine how general practitioners (GPs) communicate risk and benefit information and evidence, and integrate patient preferences. METHODS: Secondary analysis of 20 video-recorded consultations with older patients in Australian primary healthcare settings. Consultations were analysed qualitatively using the Framework method and quantitatively using the Observer OPTION5 scale and the Assessing Communication about Evidence and Patient Preferences (ACEPP) tool. RESULTS: Overall, Observer OPTION5 and ACEPP scores were low, with mean total scores of 11.3 (out of 100) and 10.4 (out of 40) respectively. Together with qualitative findings, these results suggest that shared decision-making did not occur, and that healthcare options (including anticipated benefits and risks), evidence and patient preferences were rarely discussed in our sample of consultations with older people. GPs often unilaterally made treatment decisions (usually pharmacotherapy) while patients reverted to a passive decision-making role. CONCLUSION: We observed a lack of shared decision-making in our primary care study, with little engagement of older patients in decisions about their health. PRACTICE IMPLICATIONS: Training and support tools may be needed to enhance the capacity and self-efficacy of providers and older patients to share healthcare decisions.

The NASSS framework for ex post theorisation of technology-supported change in healthcare: worked example of the TORPEDO programme.

BACKGROUND: Evaluation of health technology programmes should be theoretically informed, interdisciplinary, and generate in-depth explanations. The NASSS (non-adoption, abandonment, scale-up, spread, sustainability) framework was developed to study unfolding technology programmes in real time-and in particular to identify and manage their emergent uncertainties and interdependencies. In this paper, we offer a worked example of how NASSS can also inform ex post (i.e. retrospective) evaluation. METHODS: We studied the TORPEDO (Treatment of Cardiovascular Risk in Primary Care using Electronic Decision Support) research programme, a multi-faceted computerised quality improvement intervention for cardiovascular disease prevention in Australian general practice. The technology (HealthTracker) had shown promise in a cluster randomised controlled trial (RCT), but its uptake and sustainability in a real-world implementation phase was patchy. To explain this variation, we used NASSS to undertake secondary analysis of the multi-modal TORPEDO dataset (results and process evaluation of the RCT, survey responses, in-depth professional interviews, videotaped consultations) as well as a sample of new, in-depth narrative interviews with TORPEDO researchers. RESULTS: Ex post analysis revealed multiple areas of complexity whose influence and interdependencies helped explain the wide variation in uptake and sustained use of the HealthTracker technology: the nature of cardiovascular risk in different populations, the material properties and functionality of the technology, how value (financial and non-financial) was distributed across stakeholders in the system, clinicians' experiences and concerns, organisational preconditions and challenges, extra-organisational influences (e.g. policy incentives), and how interactions between all these influences unfolded over time. CONCLUSION: The NASSS framework can be applied retrospectively to generate a rich, contextualised narrative of technology-supported change efforts and the numerous interacting influences that help explain its successes, failures, and unexpected events. A NASSS-informed ex post analysis can supplement earlier, contemporaneous evaluations to uncover factors that were not apparent or predictable at the time but dynamic and emergent.

What drives adoption of a computerised, multifaceted quality improvement intervention for cardiovascular disease management in primary healthcare settings? A mixed methods analysis using normalisation process theory.

BACKGROUND: A computerised, multifaceted quality improvement (QI) intervention for cardiovascular disease (CVD) management in Australian primary healthcare was evaluated in a cluster randomised controlled trial. The intervention was associated with improved CVD risk factor screening but there was no improvement in prescribing rates of guideline-recommended medicines. The aim of this study was to conduct a process evaluation to identify and explain the underlying mechanisms by which the intervention did and did not have an impact. METHODS/DESIGN: Normalisation process theory (NPT) was used to understand factors that supported or constrained normalisation of the intervention into routine practice. A case study design was used in which six of the 30 participating intervention sites were purposively sampled to obtain a mix of size, governance, structure and performance. Multiple data sources were drawn on including trial outcome data, surveys of job satisfaction and team climate (68 staff) and in-depth interviews (19 staff). Data were primarily analysed within cases and compared with quantitative findings in other trial intervention and usual care sites. RESULTS: We found a complex interaction between implementation processes and several contextual factors affecting uptake of the intervention. There was no clear association between team climate, job satisfaction and intervention outcomes. There were four spheres of influence that appeared to enhance or detract from normalisation of the intervention: organisational mission and history (e.g. strategic investment to promote a QI culture enhanced cognitive participation), leadership (e.g. ability to energise or demotivate others influenced coherence), team environment (e.g. synergistic activities of team members with different skill sets influenced collective action) and technical integrity of the intervention (e.g. tools that slowed computer systems limited reflective action). DISCUSSION: Use of NPT helped explain how certain contextual factors influence the work that is done by individuals and teams when implementing a novel intervention. Although these factors do not necessarily distil into a recipe for successful uptake, they may assist system planners, intervention developers, and health professionals to better understand the trajectory that primary health care services may take when developing and engaging with QI interventions. TRIAL REGISTRATION: ACTRN 12611000478910 . Registered 08 May 2011.

Impact of Sustained Use of a Multifaceted Computerized Quality Improvement Intervention for Cardiovascular Disease Management in Australian Primary Health Care.

BACKGROUND: We evaluated a multifaceted, computerized quality improvement intervention for management of cardiovascular disease (CVD) risk in Australian primary health care. After completion of a cluster randomized controlled trial, the intervention was made available to both trial arms. Our objective was to assess intervention outcomes in the post-trial period and any heterogeneity based on original intervention allocation. METHODS AND RESULTS: Data from 41 health services were analyzed. Outcomes were (1) proportion of eligible population with guideline-recommended CVD risk factor measurements; and (2) the proportion at high CVD risk with current prescriptions for guideline-recommended medications. Patient-level analyses were conducted using generalized estimating equations to account for clustering and time effects and tests for heterogeneity were conducted to assess impact of original treatment allocation. Median follow-up for 22 809 patients (mean age, 64.2 years; 42.5% men, 26.5% high CVD risk) was 17.9 months post-trial and 35 months since trial inception. At the end of the post-trial period there was no change in CVD risk factor screening overall when compared with the end of the trial period (64.7% versus 63.5%, P=0.17). For patients at high CVD risk, there were significant improvements in recommended prescriptions at end of the post-trial period when compared with the end of the trial period (65.2% versus 56.0%, P<0.001). There was no heterogeneity of treatment effects on the outcomes based on original randomization allocation. CONCLUSIONS: CVD risk screening improvements were not observed in the post-trial period. Conversely, improvements in prescribing continued, suggesting that changes in provider and patient actions may take time when initiating medications. CLINICAL TRIAL REGISTRATION: URL: http://www.anzctr.org.au. Unique identifier: 12611000478910.

Utilisation of Medicare-funded schemes for people with cardiovascular disease.

The aim of this study is to investigate the utilisation of Medicare Benefit Scheme items for chronic disease in the management of cardiovascular disease (CVD) in general practice and to compare characteristics of CVD patients with and without a General Practice Management Plan (GPMP). Subgroup analysis of Treatment of Cardiovascular Risk using Electronic Decision Support (TORPEDO) baseline data was collected in a cohort comprising 6123 patients with CVD. The mean age (s.d.) was 71 (±13) years, 55% were male, 64% had a recorded diagnosis of coronary heart disease, 31% also had a diagnosis of diabetes and the mean number of general practice (GP) visits (s.d.) was 11 (±9) in 12 months. A total of 1955/6123 (32%) received a GPMP in the 12 months before data extraction; 1% received a Mental Health Plan. Factors associated with greater likelihood of receiving a GPMP were: younger age, had a diagnosis of diabetes, BMI > 30kgm-2, prescription of blood pressure-lowering therapy and more than ten general practice visits. Enhancing utilisation of existing schemes could augment systematic follow up and support of patients with CVD.

Effect of a computer-guided, quality improvement program for cardiovascular disease risk management in primary health care: the treatment of cardiovascular risk using electronic decision support cluster-randomized trial.

BACKGROUND: Despite effective treatments to reduce cardiovascular disease risk, their translation into practice is limited. METHODS AND RESULTS: Using a parallel arm cluster-randomized controlled trial in 60 Australian primary healthcare centers, we tested whether a multifaceted quality improvement intervention comprising computerized decision support, audit/feedback tools, and staff training improved (1) guideline-indicated risk factor measurements and (2) guideline-indicated medications for those at high cardiovascular disease risk. Centers had to use a compatible software system, and eligible patients were regular attendees (Aboriginal and Torres Strait Islander people aged ≥ 35 years and others aged ≥ 45 years). Patient-level analyses were conducted using generalized estimating equations to account for clustering. Median follow-up for 38,725 patients (mean age, 61.0 years; 42% men) was 17.5 months. Mean monthly staff support was <1 hour/site. For the coprimary outcomes, the intervention was associated with improved overall risk factor measurements (62.8% versus 53.4% risk ratio; 1.25; 95% confidence interval, 1.04-1.50; P=0.02), but there was no significant differences in recommended prescriptions for the high-risk cohort (n=10,308; 56.8% versus 51.2%; P=0.12). There were significant treatment escalations (new prescriptions or increased numbers of medicines) for antiplatelet (4.3% versus 2.7%; P=0.01), and BP lowering (18.2% versus 11.0%; P=0.02) but not lipid-lowering medications. CONCLUSIONS: In Australian primary healthcare settings, a computer-guided quality improvement intervention, requiring minimal support, improved cardiovascular disease risk measurement but did not increase prescription rates in the high-risk group. Computerized quality improvement tools offer an important, albeit partial, solution to improving primary healthcare system capacity for cardiovascular disease risk management. CLINICAL TRIAL REGISTRATION URL: https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=336630. Australian New Zealand Clinical Trials Registry No. 12611000478910.

A multifaceted quality improvement intervention for CVD risk management in Australian primary healthcare: a protocol for a process evaluation.

BACKGROUND: Cardiovascular disease (CVD) is the leading cause of death and disability worldwide. Despite the widespread availability of evidence-based clinical guidelines and validated risk predication equations for prevention and management of CVD, their translation into routine practice is limited. We developed a multifaceted quality improvement intervention for CVD risk management which incorporates electronic decision support, patient risk communication tools, computerised audit and feedback tools, and monthly, peer-ranked performance feedback via a web portal. The intervention was implemented in a cluster randomised controlled trial in 60 primary healthcare services in Australia. Overall, there were improvements in risk factor recording and in prescribing of recommended treatments among under-treated individuals, but it is unclear how this intervention was used in practice and what factors promoted or hindered its use. This information is necessary to optimise intervention impact and maximally implement it in a post-trial context. In this study protocol, we outline our methods to conduct a theory-based, process evaluation of the intervention. Our aims are to understand how, why, and for whom the intervention produced the observed outcomes and to develop effective strategies for translation and dissemination. METHODS/DESIGN: We will conduct four discrete but inter-related studies taking a mixed methods approach. Our quantitative studies will examine (1) the longer term effectiveness of the intervention post-trial, (2) patient and health service level correlates with trial outcomes, and (3) the health economic impact of implementing the intervention at scale. The qualitative studies will (1) identify healthcare provider perspectives on implementation barriers and enablers and (2) use video ethnography and patient semi-structured interviews to understand how cardiovascular risk is communicated in the doctor/patient interaction both with and without the use of intervention. We will also assess the costs of implementing the intervention in Australian primary healthcare settings which will inform scale-up considerations. DISCUSSION: This mixed methods evaluation will provide a detailed understanding of the process of implementing a quality improvement intervention and identify the factors that might influence scalability and sustainability. TRIALS REGISTRATION: 12611000478910.

Validation of a general practice audit and data extraction tool.

BACKGROUND: We assessed how accurately a common general practitioner (GP) audit tool extracts data from two software systems. METHODS: First, pathology test codes were audited at 33 practices covering nine companies. Second, a manual audit of chronic disease data from 200 random patient records at two practices was compared with audit tool data. RESULTS: Pathology review: all companies assigned correct codes for cholesterol, creatinine and glycated haemoglobin; four companies assigned incorrect codes for albuminuria tests, precluding accurate detection with the audit tool. Case record review: there was strong agreement between the manual audit and the tool for all variables except chronic kidney disease diagnoses, which was due to a tool-related programming error. DISCUSSION: The audit tool accurately detected most chronic disease data in two GP record systems. The one exception, however, highlights the importance of surveillance systems to promptly identify errors. This will maximise potential for audit tools to improve healthcare quality.

The Treatment of cardiovascular Risk in Primary care using Electronic Decision supOrt (TORPEDO) study-intervention development and protocol for a cluster randomised, controlled trial of an electronic decision support and quality improvement intervention in Australian primary healthcare.

BACKGROUND: Large gaps exist in the implementation of guideline recommendations for cardiovascular disease (CVD) risk management. Electronic decision support (EDS) systems are promising interventions to close these gaps but few have undergone clinical trial evaluation in Australia. We have developed HealthTracker, a multifaceted EDS and quality improvement intervention to improve the management of CVD risk. METHODS/DESIGN: It is hypothesised that the use of HealthTracker over a 12-month period will result in: (1) an increased proportion of patients receiving guideline-indicated measurements of CVD risk factors and (2) an increased proportion of patients at high risk will receive guideline-indicated prescriptions for lowering their CVD risk. Sixty health services (40 general practices and 20 Aboriginal Community Controlled Health Services (ACCHSs) will be randomised in a 1:1 allocation to receive either the intervention package or continue with usual care, stratified by service type, size and participation in existing quality improvement initiatives. The intervention consists of point-of-care decision support; a risk communication interface; a clinical audit tool to assess performance on CVD-related indicators; a quality improvement component comprising peer-ranked data feedback and support to develop strategies to improve performance. The control arm will continue with usual care without access to these intervention components. Quantitative data will be derived from cross-sectional samples at baseline and end of study via automated data extraction. Detailed process and economic evaluations will also be conducted. ETHICS AND DISSEMINATION: The general practice component of the study is approved by the University of Sydney Human Research Ethics Committee (HREC) and the ACCHS component is approved by the Aboriginal Health and Medical Research Council HREC. Formal agreements with each of the participating sites have been signed. In addition to the usual scientific forums, results will be disseminated via newsletters, study websites, face-to-face feedback forums and workshops. TRIAL REGISTRATION: The trial is registered with the Australian Clinical Trials Registry ACTRN 12611000478910.

Elevated plasma beta-amyloid peptide Abeta(42) levels, incident dementia, and mortality in Down syndrome.

BACKGROUND: Deposition of the beta-amyloid peptide Abeta(42) is thought to be an important initial step in the pathogenesis of Alzheimer disease (AD). Individuals with Down syndrome have increased levels of beta-amyloid peptides and an increased risk for AD. OBJECTIVE: To examine the relation of plasma levels of Abeta(42) and Abeta(40) to the risk of dementia in nondemented participants and all-cause mortality in adults with Down syndrome. DESIGN: Prospective, community-based longitudinal cohort study. SETTING: State and voluntary service providers in New York State. PARTICIPANTS: Adults with Down syndrome (N = 204). MAIN OUTCOME MEASURE: Plasma Abeta(42) and Abeta(40) levels were measured at initial examination. Participants were assessed for cognitive and functional abilities, behavioral/psychiatric conditions, and health and vital status at 14- to 18-month intervals for 4 cycles of data collection. RESULTS: Among participants who were nondemented at baseline, those in the middle and highest tertiles of plasma Abeta(42) levels were more than 2 times as likely to develop AD as those in the lowest tertile. Compared with participants without AD, participants with prevalent AD had higher levels of plasma Abeta(42) but not Abeta(40). Among all participants, those in the highest tertile of plasma Abeta(42) level at baseline were more than twice as likely to die during the study period as those in the lowest tertile, whereas there was no difference in risk of death between those in the middle and lowest tertiles of plasma Abeta(42) level. CONCLUSION: Elevations in plasma Abeta(42) peptide levels are associated with earlier onset of AD and increased risk of death.

Relation of diabetes to mild cognitive impairment.

BACKGROUND: Type 2 diabetes mellitus is an important risk factor for Alzheimer disease and is more prevalent in elderly minority persons compared with non-Hispanic white persons. OBJECTIVE: To determine whether diabetes is related to a higher risk of mild cognitive impairment (MCI), a transitional stage between normal cognition and Alzheimer disease, in a multiethnic cohort with a high prevalence of diabetes. DESIGN: Longitudinal cohort study. SETTING: Northern Manhattan in New York, NY. PARTICIPANTS: We studied persons without prevalent MCI or dementia at baseline and with at least 1 follow-up interval. Of 1772 participants with a complete neuropsychological evaluation, 339 (19.1%) were excluded because of prevalent dementia, 304 were excluded because of prevalent MCI (17.2%), and 211 were excluded because of loss to follow-up (11.9%), resulting in a final sample of 918 participants for longitudinal analyses. MAIN OUTCOME MEASURES: We related diabetes defined by self-report to incident all-cause MCI, amnestic MCI, and nonamnestic MCI. We conducted multivariate analyses with proportional hazards regression adjusting for age, sex, years of education, ethnic group, apolipoprotein E (APOE) epsilon4 allele, hypertension, low-density lipoprotein level, current smoking, heart disease, and stroke. RESULTS: A total of 334 persons had incident MCI, 160 (47.9%) had amnestic MCI, and 174 (52.1%) had nonamnestic MCI. Diabetes was related to a significantly higher risk of all-cause MCI and amnestic MCI after adjustment for all covariates. Diabetes was also related to a higher risk of nonamnestic MCI, but this association was appreciably attenuated after adjustment for socioeconomic variables and vascular risk factors. The risk of MCI attributable to diabetes was 8.8% for the whole sample and was higher for African American persons (8.4%) and Hispanic persons (11.0%) compared with non-Hispanic white persons (4.6%), reflecting the higher prevalence of diabetes in minority populations in the United States. CONCLUSION: Diabetes is related to a higher risk of amnestic MCI in a population with a high prevalence of this disorder.

Measures of adiposity and dementia risk in elderly persons.

BACKGROUND: Studies relating adiposity to dementia are conflicting. We explored the associations of body mass index (BMI), (calculated as weight in kilograms divided by the square of height in meters) waist circumference, and weight change to dementia, probable Alzheimer disease, and dementia associated with stroke (DAS). DESIGN: Persons without dementia were followed up for 5 years; 893 persons had BMI data, 907 had waist circumference data, and 709 had a second weight measurement. Dementia was ascertained using standard methods. Cox proportional hazards regression was used for analyses using follow-up as time to event, adjusting for demographics and apolipoprotein E-epsilon4 status. RESULTS: Compared with persons in the first quartile of BMI, persons in the third quartile had a lower dementia and Alzheimer disease risk and persons in the second quartile had a lower DAS risk. The association between BMI and dementia resembled a U shape in those younger than 76 years, while dementia risk decreased with higher BMI in those 76 years and older. The fourth quartile of waist circumference was related to a higher DAS risk in the whole sample, and to dementia and Alzheimer disease in persons younger than 76 years. Weight loss was related to a higher dementia and DAS risk, and weight gain was related to a higher DAS risk only. CONCLUSIONS: The prospective association between adiposity and dementia differs depending on the anthropometric measure used, and is modified by age. This may explain previous conflicting reports.

Relation between vascular risk factors and neuropsychological test performance among elderly persons with Alzheimer's disease.

BACKGROUND: Vascular risk factors increase the risk of Alzheimer's disease (AD). The mechanisms for these associations are unclear, and may be due to misdiagnosis of a vascular dementia syndrome as AD. OBJECTIVE: To examine differences in neuropsychological profile among persons diagnosed clinically with AD with and without vascular risk factors or stroke. METHODS: Community based cohort study. Individual and composite scores of neuropsychological tests at the time of clinical diagnosis of incident AD were compared among 243 persons with and without vascular risk factors or stroke. RESULTS: Among subjects with incident AD, diabetes was associated with lower performance in Delayed Recall of the Selective Reminding Test (SRT), while persons diagnosed with hypertension scored lower in consistent long term recall (CLTR) of the SRT and current smokers scored lower in Category Fluency. None of the risk factors was associated with differences in composite scores in memory, abstract/visuospatial or language domain, nor was the number of risk factors per person. Persons with stroke had a higher delayed recall score at the time of AD diagnosis. CONCLUSION: The presence of vascular risk factors among persons with clinically diagnosed AD was associated with subtle differences in neuropsychological profile at the time of diagnosis. This study needs to be replicated in samples with brain imaging, a comprehensive executive abilities battery, and pathological diagnosis of AD.

Bioavailable estradiol and age at onset of Alzheimer's disease in postmenopausal women with Down syndrome.

Several lines of evidence suggest that loss of estrogen after menopause may play a role in the cognitive declines associated with Alzheimer's disease (AD). Women with Down syndrome (DS) experience early onset of both menopause and AD. This timing provides a model to examine the influence of endogenous estrogen deficiency on risk of AD. We hypothesized that low serum levels of bioavailable estradiol (E2) would be associated with increased risk of AD. One hundred and nineteen postmenopausal women with DS, 42-59 years of age, were ascertained through the New York State developmental disability service system and followed at 18-month intervals. Information from cognitive assessments, caregiver interviews, medical record review and neurological examination was used to establish the diagnosis of dementia. Women with DS who developed AD had lower levels of bioavailable E2, lower levels of total estradiol, higher levels of sex-hormone binding globulin, and lower levels of dehydroepiandrosterone sulfate at baseline than women who remained dementia free over the course of follow-up. Women who had low levels of bioavailable E2 at baseline were four times as likely to develop AD (HR=4.1, 95% CI: 1.2-13.9) and developed AD, on average, 3 years earlier, than those with high levels of bioavailable E2, after adjustment for age, level of mental retardation, ethnicity, body mass index, history of hypothyroidism or depression and the presence of the apolipoprotein varepsilon4 allele. Our findings support the hypothesis that reductions in estrogen following menopause can contribute to the cascade of pathological processes leading to AD.

Increased serum neopterin levels in adults with Down syndrome.

We quantitated serum neopterin levels in Down syndrome (DS), normal controls, Alzheimer's disease, multiple sclerosis and other neurological diseases. We then analyzed the relationships with age, sex, apolipoprotein E (Apo E) phenotype, and amyloid beta protein 1-40 (Abeta40) and 1-42 (Abeta42) levels. Neopterin levels were higher in DS than all other groups. Levels in young DS (< 40 years of age) and old DS (> 41 years) were similar. There was no significant correlation between neopterin levels and age, sex, Apo E phenotype, and Abeta40 or Abeta42 levels in DS. This lack of correlation between neopterin and Abeta levels suggests that the higher neopterin concentrations in DS group reflect inflammatory cell activation rather than AD neuropathology.

Obesity enhances verbal memory in postmenopausal women with Down syndrome.

Several lines of evidence suggest that the loss of estrogen after menopause may play a role in cognitive declines associated with Alzheimer's disease (AD). In postmenopausal women, the principal source of estrogen is estrone, which is influenced by body mass index (BMI). Increased BMI in postmenopausal women is associated with higher levels of serum estradiol and estrone. We hypothesized that obesity could have a beneficial effect on cognition with advancing age. We compared the performance of healthy nondemented obese and non-obese women with Down syndrome (DS) on a broad spectrum of cognitive tests. Estrone levels were 66.9% higher in obese than in non-obese postmenopausal women, and 136% higher in obese than in non-obese premenopausal women. Obese postmenopausal women performed significantly better than non-obese women on measures of verbal memory and on an omnibus test of neuropsychological function, but did not differ significantly in verbal fluency, language, praxis or visuospatial functioning. Among premenopausal women, there was no difference in cognitive function between obese and non-obese women. Our results support the hypothesis that higher endogenous estrogen levels after menopause are associated with better performance on verbal memory.