Heterogeneity in Risk Factors for Cognitive Impairment, No Dementia: Population-Based Longitudinal Study From the Kungsholmen Project

2007 ◽  
Vol 15 (1) ◽  
pp. 60-69 ◽  
Author(s):  
Roberto Monastero ◽  
Katie Palmer ◽  
Chengxuan Qiu ◽  
Bengt Winblad ◽  
Laura Fratiglioni
Author(s):  
J. Skov Neergaard ◽  
K. Dragsbæk ◽  
C. Christiansen ◽  
M. Asser Karsdal ◽  
S. Brix ◽  
...  

Background: Identification of subjects with a progressive disease phenotype is an urgent need in the pharmaceutical industry where most of the recent clinical trials in Alzheimer’s disease have failed. Objectives: The objective of this study was to identify subgroups of individuals with objective cognitive impairment (OCI), who were most likely to progress to dementia and to identify the risk factors associated with progression. Design: Prospective cohort study. Setting: Population-based. Participants: 5,380 elderly women from Denmark. Measurements: The Short Blessed Test and a category fluency test with animal naming, was used to assess cognitive function, and to classify them into different groups of OCI. Results: OCI was identified in 852 subjects at baseline. The risk of dementia was elevated for OCI subjects as compared to subjects with normal cognition (HR 1.46[1.19-1.79]). The courses of OCI were studied in a sub-cohort who completed the cognitive assessment at both the baseline and the follow-up visit (n = 1,933). Of these subjects 203 had OCI at baseline. The multi-domain subtypes of OCI were associated with progressive OCI. Subjects most likely to progress were older, physically inactive, had a higher level of total cholesterol (>6.5 mmol/L) and had a history of depression as compared to subjects with a non-progressive course of OCI. Conclusions: In this cohort we identified a risk profile associated with progression from OCI in older women. The degree of impairment at baseline was an important predictor of conversion to dementia, additionally several modifiable risk factors were associated with progression.


Author(s):  
Dawn Everington ◽  
Zhiqiang Feng ◽  
Kevin Ralston ◽  
Chris Dibben

BackgroundThe high level of young people not in education, employment or training (NEET) has been an important long-standing issue in Scotland. The experience of being NEET has long term detrimental effects. Main AimIdentify risk factors that could inform interventions aimed at reducing the number of NEETs. MethodsWe use the Scottish Longitudinal Study (SLS) which provides a 5.3% representative sample of Scotland’s population based around the Censuses of 1991, 2001 and 2011. The SLS includes Vital Event data, Census data for the SLS sample and also those living in the same household and, since 2007, school census data. This allows us to study two cohorts of 16-19 year olds (the ages used in Scotland when considering NEET status) over a period of 10 years: those 6-9 years old at the time of the 1991 Census to the 2001 Census when they were 16-19 years old those 6-9 years old at the time of the 2001 Census to the 2011 Census when they were 16-19 years old We used logistic regression to investigate whether NEET status is associated with individual, family and household characteristics measured 10 years previously and later data including school qualification, school behaviour, areal characteristics and teenage pregnancy. ResultsThese analyses found several factors were associated with the likelihood of being NEET for both cohorts, including having no qualifications, teenage pregnancy and living in an area where there was a relatively high level of NEETs (100% census data). For the later cohort, school census data were available and school behaviour were important factors, whereas household characteristics at childhood were important factors for the earlier cohort. ConclusionA number of factors are associated with NEET but those closer in time to the NEET ages of 16-19 appear to be more important than childhood factors.


Neurology ◽  
2013 ◽  
Vol 80 (23) ◽  
pp. 2112-2120 ◽  
Author(s):  
M. Ganguli ◽  
B. Fu ◽  
B. E. Snitz ◽  
T. F. Hughes ◽  
C.-C. H. Chang

1999 ◽  
Vol 9 (2) ◽  
pp. 163-182 ◽  
Author(s):  
DWK Kay

The last five years have produced a large output on the epidemiology of dementia and cognitive impairment, specially on apolipoprotein E (apo E), vascular changes, and education as risk factors. Minor cognitive deficits have been studied prospectively to assess their value in predicting dementia. Reviews of work from particular centres and articles on special aspects give more detail. Preference is given to population-based over clinic-based studies and to those published in or after 1994.


2009 ◽  
Vol 22 (2) ◽  
pp. 291-299 ◽  
Author(s):  
Graciela Muniz Terrera ◽  
Carol Brayne ◽  
Fiona Matthews ◽  

ABSTRACTBackground: Cognitive decline in old age varies among individuals. The identification of groups of individuals with similar patterns of cognitive change over time may improve our ability to see whether the effect of risk factors is consistent across groups.Methods: Whilst accounting for the missing data, growth mixture models (GMM) were fitted to data from four interview waves of a population-based longitudinal study of aging, the Cambridge City over 75 Cohort Study (CC75C). At all interviews global cognition was assessed using the Mini-mental State Examination (MMSE).Results: Three patterns were identified: a slow decline with age from a baseline of cognitive ability (41% of sample), an accelerating decline from a baseline of cognitive impairment (54% of sample) and a steep constant decline also from a baseline of cognitive impairment (5% of sample). Lower cognitive scores in those with less education were seen at baseline for the first two groups. Only in those with good performance and steady decline was the effect of education strong, with an increased rate of decline associated with poor education. Good mobility was associated with higher initial score in the group with accelerating change but not with rate of decline.Conclusion: Using these analytical methods it is possible to detect different patterns of cognitive change with age. In this investigation the effect of education differs with group. To understand the relationship of potential risk factors for cognitive decline, careful attention to dropout and appropriate analytical methods, in addition to long-term detailed studies of the population points, are required.


Sign in / Sign up

Export Citation Format

Share Document