Comorbidity and dementia: a scoping review of the literature.

BACKGROUND: Evidence suggests that amongst people with dementia there is a high prevalence of comorbid medical conditions and related complaints. The presence of dementia may complicate clinical care for other conditions and undermine a patient's ability to manage a chronic condition. The aim of this study was to scope the extent, range and nature of research activity around dementia and comorbidity. METHODS: We undertook a scoping review including all types of research relating to the prevalence of comorbidities in people with dementia; current systems, structures and other issues relating to service organisation and delivery; patient and carer experiences; and the experiences and attitudes of service providers. We searched AMED, Cochrane Library, CINAHL, PubMed, NHS Evidence, Scopus, Google Scholar (searched 2012, Pubmed updated 2013), checked reference lists and performed citation searches on PubMed and Google Scholar (ongoing to February 2014). RESULTS: We included 54 primary studies, eight reviews and three guidelines. Much of the available literature relates to the prevalence of comorbidities in people with dementia or issues around quality of care. Less is known about service organisation and delivery or the views and experiences of people with dementia and their family carers. There is some evidence that people with dementia did not have the same access to treatment and monitoring for conditions such as visual impairment and diabetes as those with similar comorbidities but without dementia. CONCLUSIONS: The prevalence of comorbid conditions in people with dementia is high. Whilst current evidence suggests that people with dementia may have poorer access to services the reasons for this are not clear. There is a need for more research looking at the ways in which having dementia impacts on clinical care for other conditions and how the process of care and different services are adapting to the needs of people with dementia and comorbidity. People with dementia should be included in the debate about the management of comorbidities in older populations and there needs to be greater consideration given to including them in studies that focus on age-related healthcare issues

What controls gain in gain control? Mismatch negativity (MMN), priors and system biases

Repetitious patterns enable the auditory system to form prediction models specifying the most likely characteristics of subsequent sounds. Pattern deviations elicit mismatch negativity (MMN), the amplitude of which is modulated by the size of the deviation and confidence in the model. Todd et al. (2001; 2013) demonstrated that a multi-timescale sequence reveals a bias that profoundly distorts the impact of local sound statistics on the MMN amplitude. Two sounds alternate roles as repetitious “standard” and rare “deviant” rapidly (every 0.8 minutes) or slowly (every 2.4 minutes). The bias manifests as larger MMN to the sound first encountered as deviant in slow compared to fast changing sequences, but no difference for the sound first encountered as a standard. We propose that the bias is due to how Bayesian priors shape filters of sound relevance. By examining the time-course of change in MMN amplitude we show that the bias manifests immediately after roles change but rapidly disappears thereafter. The bias was reflected in the response to deviant sounds only (not in response to standards), consistent with precision estimates extracted from second order patterns modulating gain differentially for the two sounds.. Evoked responses to deviants suggest that pattern extraction and reactivation of priors can operate over tens of minutes or longer. Both MMN and deviant responses establish that: (1) priors are defined by the most proximally encountered probability distribution when one exists but; (2) when no prior exists, one is instantiated by sequence onset characteristics; and (3) priors require context interruption to be updated

Health inequalities among older men and women in Africa and Asia : evidence from eight Health and Demographic Surveillance System sites in the INDEPTH WHO-SAGE Study

Background: Declining rates of fertility and mortality are driving demographic transition in all regions of the world, leading to global population ageing and consequently changing patterns of global morbidity and mortality. Understanding sex-related health differences, recognising groups at risk of poor health and identifying determinants of poor health are therefore very important for both improving health trajectories and planning for the health needs of ageing populations. Objectives: To determine the extent to which demographic and socio-economic factors impact upon measures of health in older populations in Africa and Asia; to examine sex differences in health and further explain how these differences can be attributed to demographic and socio-economic determinants. Methods: A total of 46,269 individuals aged 50 years and over in eight Health and Demographic Surveillance System (HDSS) sites within the INDEPTH Network were studied during 2006-2007 using an abbreviated version of the WHO Study on global AGEing and adult health (SAGE) Wave I instrument The survey data were then linked to longitudinal HDSS background information. A health score was calculated based on self-reported health derived from eight health domains. Multivariable regression and post-regression decomposition provide ways of measuring and explaining the health score gap between men and women. Results: Older men have better self-reported health than older women. Differences in household socioeconomic levels, age, education levels, marital status and living arrangements explained from about 82% and 71% of the gaps in health score observed between men and women in South Africa and Kenya, respectively, to almost nothing in Bangladesh. Different health domains contributed differently to the overall health scores for men and women in each country. Conclusion: This study confirmed the existence of sex differences in self-reported health in low- and middleincome countries even after adjustments for differences in demographic and socio-economic factors. A decomposition analysis suggested that sex differences in health differed across the HDSS sites, with the greatest level of inequality found in Bangladesh. The analysis showed considerable variation in how differences in socio-demographic and economic characteristics explained the gaps in self-reported health observed between older men and women in African and Asian settings. The overall health score was a robust indicator of health, with two domains, pain and sleep/energy, contributing consistently across the HDSS sites. Further studies are warranted to understand other significant individual and contextual determinants to which these sex differences in health can be attributed. This will lay a foundation for a more evidence-based approach to resource allocation, and to developing health promotion programmes for older men and women in these settings.Financial support was provided by the US National Institute on Aging through an interagency agreement with the World Health Organization, supplemented by support from Umea University for the Filabavi and Purworejo sites. Both WHO and INDEPTH contributed financial and human resources to the collaboration. The Umea Centre for Global Health Research (supported by FAS, the Swedish Council for Working Life and Social Research, Grant No. 2006-1512) provided technical support and advice to the sites and co-hosted with INDEPTH an analytic and writing workshop in 2008. The Health and Population Division, School of Public Health, University of the Witwatersrand, South Africa serves as the satellite secretariat providing scientific leadership, technical and administrative support for the INDEPTH Adult Health and Ageing initiative.</p