The Epidemiology of Cognitive Function In a Community Based Population. The EPIC-Norfolk Study

Although age is the strongest known risk factor, not all people who reach old age develop dementia before they die. Recommendations on potentially modifiable risk factors for the prevention of dementia are based on evidence that is, at best, moderate in strength. There are major calls to strengthen the evidence on potentially modifiable risk factors of dementia. The European Prospective Investigation into Cancer in Norfolk (EPIC-Norfolk) is a prospective population study of 25 639 men and women aged 40–79 years first recruited in 1993-1997, who attended a health examination. Subsequent follow-ups have involved self-report of health and lifestyle and further health examinations. Cognitive measures (7 tests assessing a range of domains) were introduced as part of a third health examination between 2006 and 2011 (including data from a pilot phase 2004–2006) and are available on 8585 individuals. Almost complete follow-up for disease outcomes, including dementia and mortality, has been established via linkage to health records. Education was strongly associated with cognitive function for all abilities tested. Cross-sectional and prospective analyses showed those who were physically inactive during work, were less likely to have poor cognition (bottom tenth percentile of a composite cognition score); Odds Ratio (OR) = 0.68 (95% Confidence Interval or CI 0.54, 0.86 P=0.001). In contrast, inactivity during leisure time was associated with increased risk of poor performance in the cross-sectional analyses, although this association was not observed in the prospective analyses. Poor cognition was independently associated with higher risk of all-cause mortality and predictive of incident dementia. Associations were observed for the composite score (global cognition) as well as specific cognitive abilities. Poor cognition in four or more tests was associated with ten-fold increased risk of developing dementia compared with those who did not perform poorly in any test OR=10.82 (95% CI 6.85, 17.10 P<0.001). Addition of each cognitive measure strengthened prediction models of dementia further, Area under the curve (AUC) = 0.85 (95% CI 0.82, 0.87 P<0.001), with the single test for episodic memory having the strongest influence. Routinely collected health records are increasingly encouraged and used for epidemiological research for dementia outcome ascertainment. The linkage of the cohort to diverse routine records enabled comparison of these data sources. I provide evidence for the need of a more consensus-based approach to the methods of data collection, coding and interpretation of health data across all sources examined (hospital inpatient, mortality and mental health services datasets). In summary, the findings from this dissertation suggest the relationships between lifestyle factors, poor cognition and dementia are complex. For stronger evidence, future studies need to account for characteristics of the sample population and for the test used to measure cognition. Furthermore, there is a need for a more nuanced approach to the way the exposure of interest as well as dementia outcomes are measured and to adequately address the issue of potential confounding

Predicting admissions and time spent in hospital over a decade in a population-based record linkage study: the EPIC-Norfolk cohort.

OBJECTIVE: To quantify hospital use in a general population over 10 years follow-up and to examine related factors in a general population-based cohort. DESIGN: A prospective population-based study of men and women. SETTING: Norfolk, UK. PARTICIPANTS: 11,228 men and 13,786 women aged 40-79 years in 1993-1997 followed between 1999 and 2009. MAIN OUTCOMES MEASURES: Number of hospital admissions and total bed days for individuals over a 10-year follow-up period identified using record linkage; five categories for admissions (from zero to highest ≥ 7) and hospital bed days (from zero to highest ≥ 20 nights). RESULTS: Over a period of 10 years, 18,179 (72.7%) study participants had at least one admission to hospital, 13.8% with 7 or more admissions and 19.9% with 20 or more nights in hospital. In logistic regression models with outcome ≥ 7 admissions, low education level OR 1.14 (1.05 to 1.24), age OR per 10-year increase 1.75 (1.67 to 1.82), male sex OR 1.32 (1.22 to 1.42), manual social class 1.22 (1.13 to 1.32), current cigarette smoker OR 1.53 (1.37 to 1.71) and body mass index >30 kg/m² OR 1.41 (1.28 to 1.56) all independently predicted the outcome with p30 kg/m², estimated percentages of the cohort in the categories of admission numbers and hospital bed days in stratified age bands with twofold to threefold differences in future hospital use between those with high-risk and low-risk scores. CONCLUSIONS: The future probability of cumulative hospital admissions and bed days appears independently related to a range of simple demographic and behavioural indicators. The strongest of these is increasing age with high body mass index and smoking having similar magnitudes for predicting risk of future hospital usage.The design and conduct of the EPIC-Norfolk study and collection and management of the data was supported by programme grants from the Medical Research Council UK (G9502233, G0401527) and Cancer Research UK (C864/A8257, C864/A2883).This is the final version of the article. It first appeared from the BMJ Group via http://dx.doi.org/10.1136/bmjopen-2015-00946

The Relationship Between Cognitive Performance Using Tests Assessing a Range of Cognitive Domains and Future Dementia Diagnosis in a British Cohort: A Ten-Year Prospective Study.

BACKGROUND: Exploring the domains of cognitive function which are most strongly associated with future dementia may help with understanding risk factors for, and the natural history of dementia. OBJECTIVE: To examine the association of performance on a range of cognitive tests (both global and domain specific) with subsequent diagnosis of dementia through health services in a population of relatively healthy men and women and risk of future dementia. METHODS: We examined the association between performance on different cognitive tests as well as a global score and future dementia risk ascertained through health record linkage in a cohort of 8,581 individuals (aged 48-92 years) between 2004-2019 with almost 15 years follow-up (average of 10 years) before and after adjustment for socio-demographic, lifestyle, and health characteristics. RESULTS: Those with poor performance for global cognition (bottom 10%) were almost four times as likely to receive a dementia diagnosis from health services over the next 15 years than those who performed well HR = 3.51 (95% CI 2.61, 4.71 p < 0.001) after adjustment for socioeconomic, lifestyle, and biological factors and also prevalent disease. Poor cognition performance in multiple tests was associated with 10-fold increased risk compared to those not performing poorly in any test HR = 10.82 (95% CI 6.85, 17.10 p < 0.001). CONCLUSION: Deficits across multiple cognitive domains substantially increase risk of future dementia over and above neuropsychological test scores ten years prior to a clinical diagnosis. These findings may help further understanding of the natural history of dementia and how such measures could contribute to strengthening future models of dementia.This work was supported by the Medical Research Council, UK (MRC) http://www.mrc.ac.uk/ (Ref: MR/N003284/1) Cancer Research UK http://www.cancerresearchuk. org/ (CRUK, Ref: C864/A8257) and NIHR https://www.nihr.ac.uk (Ref: NF-SI-0616-10090 to [CB]). The clinic for EPIC- Norfolk 3HC was funded by Research into Aging, now known as Age UK http://www.ageuk.org.uk/ (Grant Ref: 262). The pilot phase was supported by MRC (Ref: G9502233) and CRUK (Ref: C864/ A2883)

Cross-sectional and prospective relationship between occupational and leisure time inactivity and cognitive function in an ageing population. The European Prospective Investigation into Cancer and Nutrition in Norfolk (EPIC-Norfolk) Study.

Background: The current evidence for higher physical activity and better cognitive function and lower risk of dementia is strong but not conclusive. More robust evidence is needed to inform public health policy. We provide further insight to discrepancies observed across studies, reporting on habitual inactivity including that during work. Methods: We examined cross-sectional and prospective relationships of physical inactivity during leisure and occupation time, with cognitive performance using a validated physical activity index in a cohort of 8585 men and women aged 40-79 years at baseline (1993-1997) for different domains using a range of cognitive measures. Cognitive testing was conducted between 2006-2011 (including pilot phase 2004-2006). Associations were examined using multinomial logistic regression adjusting for socio-demographic and health variables as well total habitual physical activity. Results: Inactivity during work was inversely associated with poor cognitive performance (bottom tenth percentile of a composite cognition score); Odds Ratio (OR) = 0·68 (95% Confidence Interval (CI) 0.54, 0·86) P=0·001. Results were similar cross-sectionally; OR = 0·65 (95% CI 0·45, 0·93) P=0·02. Manual workers had increased risk of poor performance compared to those with an occupation classified as inactive. Inactivity during leisure time was associated with increased risk of poor performance in the cross-sectional analyses only. Conclusions: The relationship between inactivity and cognition is strongly confounded by education, social class and occupation. Physical activity during leisure may be protective for cognition, but work related physical activity is not protective. A greater understanding of the mechanisms and confounding underlying these paradoxical findings is needed.This work was supported by the Medical Research Council, UK (MRC) http://www.mrc.ac.uk/ (Ref: MR/N003284/1, MC-UU_12015/1 to N.W.); Cancer Research UK, http://www.cancerresearchuk.org/ (CRUK, Ref: C864/A8257) and NIHR, https://www.nihr.ac.uk (Ref: NF-SI-0616–10090 to C.B.). The clinic for EPIC- orfolk 3HC was funded by Research into Ageing, now known as Age UK, http://www.ageuk.org.uk/ (Grant Ref: 262). The pilot phase was supported by MRC (Ref: G9502233) and CRUK (Ref: C864/A2883

Sociodemographic and lifestyle predictors of incident hospital admissions with multimorbidity in a general population, 1999-2019: the EPIC-Norfolk cohort.

BACKGROUND:The ageing population and prevalence of long-term disorders with multimorbidity are a major health challenge worldwide. The associations between comorbid conditions and mortality risk are well established; however, few prospective community-based studies have reported on prior risk factors for incident hospital admissions with multimorbidity. We aimed to explore the independent associations for a range of demographic, lifestyle and physiological determinants and the likelihood of subsequent hospital incident multimorbidity. METHODS:We examined incident hospital admissions with multimorbidity in 25 014 men and women aged 40-79 in a British prospective population-based study recruited in 1993-1997 and followed up until 2019. The determinants of incident multimorbidity, defined as Charlson Comorbidity Index ≥3, were investigated using multivariable logistic regression models for the 10-year period 1999-2009 and repeated with independent measurements in a second 10-year period 2009-2019. RESULTS:Between 1999 and 2009, 18 179 participants (73% of the population) had a hospital admission. Baseline 5-year and 10-year incident multimorbidities were observed in 6% and 12% of participants, respectively. Age per 10-year increase (OR 2.19, 95% CI 2.06 to 2.33) and male sex (OR 1.32, 95% CI 1.19 to 1.47) predicted incident multimorbidity over 10 years. In the subset free of the most serious diseases at baseline, current smoking (OR 1.86, 95% CI 1.60 to 2.15), body mass index >30 kg/m² (OR 1.48, 95% CI 1.30 to 1.70) and physical inactivity (OR 1.16, 95% CI 1.04 to 1.29) were positively associated and plasma vitamin C (a biomarker of plant food intake) per SD increase (OR 0.86, 95% CI 0.81 to 0.91) inversely associated with incident 10-year multimorbidity after multivariable adjustment for age, sex, social class, education, alcohol consumption, systolic blood pressure and cholesterol. Results were similar when re-examined for a further time period in 2009-2019. CONCLUSION:Age, male sex and potentially modifiable lifestyle behaviours including smoking, body mass index, physical inactivity and low fruit and vegetable intake were associated with increased risk of future incident hospital admissions with multimorbidity

Lower Mental Health Related Quality of Life Precedes Dementia Diagnosis : findings from the EPIC-Norfolk prospective population-based study.

Acknowledgements The EPIC-Norfolk study (DOI 10.22025/2019.10.105.00004) has received funding from the Medical Research Council (MR/N003284/1, MC-UU_12015/1 and MC_UU_00006/1) and Cancer Research UK (C864/A14136). We are grateful to all the participants and participating GP practices who have been part of the project, and to the many members of the study team at the University of Cambridge who have enabled this researchPeer reviewe

Residential area deprivation and risk of subsequent hospital admission in a British population: the EPIC-Norfolk cohort.

OBJECTIVES:To investigate whether residential area deprivation index predicts subsequent admissions to hospital and time spent in hospital independently of individual social class and lifestyle factors. DESIGN:Prospective population-based study. SETTING:The European Prospective Investigation into Cancer in Norfolk (EPIC-Norfolk) study. PARTICIPANTS:11 214 men and 13 763 women in the general population, aged 40-79 years at recruitment (1993-1997), alive in 1999. MAIN OUTCOME MEASURE:Total admissions to hospital and time spent in hospital during a 19-year time period (1999-2018). RESULTS:Compared to those with residential Townsend Area Deprivation Index lower than the average for England and Wales, those with a higher than average deprivation index had a higher likelihood of spending >20 days in hospital multivariable adjusted OR 1.18 (95% CI 1.07 to 1.29) and having 7 or more admissions OR 1.11 (95% CI 1.02 to 1.22) after adjustment for age, sex, smoking status, education, social class and body mass index. Occupational social class and educational attainment modified the association between area deprivation and hospitalisation; those with manual social class and lower education level were at greater risk of hospitalisation when living in an area with higher deprivation index (p-interaction=0.025 and 0.020, respectively), while the risk for non-manual and more highly educated participants did not vary greatly by area of residence. CONCLUSION:Residential area deprivation predicts future hospitalisations, time spent in hospital and number of admissions, independently of individual social class and education level and other behavioural factors. There are significant interactions such that residential area deprivation has greater impact in those with low education level or manual social class. Conversely, higher education level and social class mitigated the association of area deprivation with hospital usage

Crowdsourcing as a novel technique for retinal fundus photography classification: analysis of images in the EPIC Norfolk cohort on behalf of the UK Biobank Eye and Vision Consortium.

AIM: Crowdsourcing is the process of outsourcing numerous tasks to many untrained individuals. Our aim was to assess the performance and repeatability of crowdsourcing for the classification of retinal fundus photography. METHODS: One hundred retinal fundus photograph images with pre-determined disease criteria were selected by experts from a large cohort study. After reading brief instructions and an example classification, we requested that knowledge workers (KWs) from a crowdsourcing platform classified each image as normal or abnormal with grades of severity. Each image was classified 20 times by different KWs. Four study designs were examined to assess the effect of varying incentive and KW experience in classification accuracy. All study designs were conducted twice to examine repeatability. Performance was assessed by comparing the sensitivity, specificity and area under the receiver operating characteristic curve (AUC). RESULTS: Without restriction on eligible participants, two thousand classifications of 100 images were received in under 24 hours at minimal cost. In trial 1 all study designs had an AUC (95%CI) of 0.701(0.680-0.721) or greater for classification of normal/abnormal. In trial 1, the highest AUC (95%CI) for normal/abnormal classification was 0.757 (0.738-0.776) for KWs with moderate experience. Comparable results were observed in trial 2. In trial 1, between 64-86% of any abnormal image was correctly classified by over half of all KWs. In trial 2, this ranged between 74-97%. Sensitivity was ≥ 96% for normal versus severely abnormal detections across all trials. Sensitivity for normal versus mildly abnormal varied between 61-79% across trials. CONCLUSIONS: With minimal training, crowdsourcing represents an accurate, rapid and cost-effective method of retinal image analysis which demonstrates good repeatability. Larger studies with more comprehensive participant training are needed to explore the utility of this compelling technique in large scale medical image analysis

Crowdsourcing as a screening tool to detect clinical features of glaucomatous optic neuropathy from digital photography.

AIM: Crowdsourcing is the process of simplifying and outsourcing numerous tasks to many untrained individuals. Our aim was to assess the performance and repeatability of crowdsourcing in the classification of normal and glaucomatous discs from optic disc images. METHODS: Optic disc images (N = 127) with pre-determined disease status were selected by consensus agreement from grading experts from a large cohort study. After reading brief illustrative instructions, we requested that knowledge workers (KWs) from a crowdsourcing platform (Amazon MTurk) classified each image as normal or abnormal. Each image was classified 20 times by different KWs. Two study designs were examined to assess the effect of varying KW experience and both study designs were conducted twice for consistency. Performance was assessed by comparing the sensitivity, specificity and area under the receiver operating characteristic curve (AUC). RESULTS: Overall, 2,540 classifications were received in under 24 hours at minimal cost. The sensitivity ranged between 83-88% across both trials and study designs, however the specificity was poor, ranging between 35-43%. In trial 1, the highest AUC (95%CI) was 0.64(0.62-0.66) and in trial 2 it was 0.63(0.61-0.65). There were no significant differences between study design or trials conducted. CONCLUSIONS: Crowdsourcing represents a cost-effective method of image analysis which demonstrates good repeatability and a high sensitivity. Optimisation of variables such as reward schemes, mode of image presentation, expanded response options and incorporation of training modules should be examined to determine their effect on the accuracy and reliability of this technique in retinal image analysis

Usual physical activity and subsequent hospital usage over 20 years in a general population: the EPIC-Norfolk cohort

Abstract: Background: While physical activity interventions have been reported to reduce hospital stays, it is not clear if, in the general population, usual physical activity patterns may be associated with subsequent hospital use independently of other lifestyle factors. Objective: We examined the relationship between reported usual physical activity and subsequent admissions to hospital and time spent in hospital for 11,228 men and 13,786 women aged 40–79 years in the general population. Methods: Participants from a British prospective population-based cohort study were followed for 20 years (1999–2019) using record linkage to document hospital usage. Total physical activity was estimated by combining workplace and leisure time activity reported in a baseline lifestyle questionnaire and repeated in a subset at a second time point approximately 12 years later. Results: Compared to those reporting no physical activity, participants who were the most active had a lower likelihood of spending more than 20 days in hospital odds ratio (OR) 0.88 (95% confidence interval (CI) 0.81–0.96) over the next 20 years after multivariable adjustment for age, sex, smoking status, education, social class and body mass index. Participants reporting any activity had a mean of 0.42 fewer hospital days per year between 1999 and 2009 compared to inactive participants, an estimated potential saving to the National Health Service (NHS) of £247 per person per year, or approximately 7% of UK health expenditure. Participants who remained physically active or became active 12 years later had lower risk of subsequent hospital usage than those who remained inactive or became inactive, p-trend < 0.001. Conclusion: Usual physical activity in this middle-aged and older population predicts lower future hospitalisations - time spent in hospital and number of admissions independently of behavioural and sociodemographic factors. Small feasible differences in usual physical activity in the general population may potentially have a substantial impact on hospital usage and costs