1. Sleep disturbances and cognitive function in the English Longitudinal Study of Ageing (ELSA) Michelle A. Miller ESRC Oxford Research Methods Festival St. Catherine’s College, Oxford, 8-10°July 2014 University of Warwick, ‘Sleep, Health & Society Programme’ Warwick Medical School, Coventry, UK

2. Overview Background / setting Study aim Methodological considerations with reference to SDAI Results Limitations Conclusions

3. Background setting Sleep disturbances are important predictors of ill-health Cognitive decline common in older age (Bozoki et al, 2013) 1 in 9 develop Alzheimer’s by age 75yrs (McDowell, 2001) Dementia affects ~800,000 people in the UK Is Sleep a risk factor? Explore using SDAI Utilise ELSA 3

4. Sleep and cognition in an ageing population. The English Longitudinal Study of Ageing (ELSA) Aims: To assess the evidence for associations between sleep quantity and quality and amnestic and non-amnestic cognitive function. Hypotheses: Poor quality and short/long sleepers will have poorer cognitive function than optimal sleepers Amnestic and non-amnestic functions may be affected differently by poor sleep. 4

5. Methodological considerations for secondary data analysis Population Representative Size and Power Confounders Exposure and outcome measures Follow-up data Study design 5

6. The English Longitudinal Study of Ageing (ELSA) Cohort Panel study: Population –Cohort of men and women aged ≥50 years –Started in 2002, follow up every 2 years –Computer-assisted personal interview, self-completion questionnaire, nurse visit Representative –UK representative sample –ELSA is harmonized with ageing studies in other countries to facilitate international comparisons. A Steptoe, et al.Int J Epidemiol. 2013 Dec;42(6):1640-8..

7. Methodological considerations for secondary data analysis Population Representative Size and Power Confounders Exposure and outcome measures Follow-up data Study design 7

8. The English Longitudinal Study of Ageing (ELSA) Size and power –Original sample N = 11,391 Confounders –Economic, social, psychological, cognitive, health, biological and, genetic data –Linked to financial and health registry data The data set is openly available to researchers and analysts (http://www.esds.ac.uk/longitudinal/access/elsa/l5050.asp). A Steptoe, et al.Int J Epidemiol. 2013 Dec;42(6):1640-8..

9. Methodological considerations for secondary data analysis Population Representative Size and Power Confounders Exposure and outcome measures Follow-up data Study design 9

10. Exposure and Outcome 10 Analysis of covariance (ANCOVA)

11. Is the exposure robust and valid? LimitationsAdvantages Sleep Quantity How many hours sleep do you get on an average week night? Questionnaire based (self- reported sleep) Large number of responders Free response (continuous or categorical data) Sleep Quality How frequently do you: i) Have difficulty falling asleep ii) Wake up several times in the night iii) Wake up feeling tired and worn out 1 = Not in past month; 2 = Less than once a week; 3 = Once or twice a week; 4 = Three or more per week iv) Self-rated sleep quality 1 = Very good; 2 = Good; 3 = Fairly bad; 4 = Very bad Questionnaire based (Self- reported) Multiple components of Sleep quality recorded 11

12. Is the outcome robust and valid? AmnesticNon-amnestic Orientation in time - Date questions. Can you tell me“todays date” Word learning and recall - 10 words; immediate and delayed recall Prospective memory - ‘Remembering to remember’. Instructions for later task e.g. to write initials on paper. Word finding (verbal fluency) -Naming animals Eg. Name as many different animals as you can in one minute. Letter cancellation -Attention, mental speed & visual scanning Numeracy - Mental arithmetic 12

13. Methodological considerations for secondary data analysis Population Representative Size and Power Confounders Exposure and outcome measures Follow-up data Study design 13

14. English Longitudinal Study of Ageing (ELSA) Prospective population panel study of British men and women, aged 50+ years Wave 1 (2002/3) N = 12,099 Main interview (inc. cognition) Wave 2 (2004/5) N = 9,432 Main interview (inc. cognition) Nurse visit Wave 3 (2006/7) N = 9,771 Main interview (inc. cognition) Wave 4 (2008/9) N = 11,050 Main interview (inc. cognition) Nurse visit Sleep data Wave 5 (2010/11) N = 10,275 (approx) Main interview (inc. cognition) ESRC SDAI Phase 1 “Sleep disturbances and cognition in ELSA” ESRC SDAI Phase 2 Prospective analysis (application pending)

15. Results 15 YOUNGER (50-64 years) OLDER (65+ years) < 6hr6 - 8hr> 8hrp< 6hr6 - 8hr> 8hrp2p2 N [%] 646 [13.9] 3778 [81.1] 236 [5.1] 607 [14.7] 3136 [76.0] 386 [9.3] Sex (% male) 37.346.238.6<0.00137.447.545.3<0.001 Age (years) 57.9 (3.8) 58.3 (4.2)=0.25273.9 (6.1)73.2 (6.1)74.5 (6.5)<0.001 Amn (T score) 48.4 (6.3)50.4 (6.2)48.6 (6.9)<0.00149.4 (6.6)50.4 (6.7)47.5 (8.4)<0.001 Non-amn (T score) 48.8 (5.5)50.3 (5.4)48.4 (5.8)<0.00149.2 (5.7)50.4 (6.0)48.3 (6.2)<0.001 Results expressed as mean (SD) or %. ] ] ANOVA for continuous data, chi-square for categorical data (where p value represents differences between all categories) Miller et al., PLOS ONE 2014 (In press)  Significant interactions were detected between sleep disturbances (quantity and quality) and age.  Responders were separated into younger (50-64 years; n= 4,660) and older (65+ years; n= 4,129).

16. Fully adjusted amnestic and non-amnestic function T-scores by sleep quantity and quality 16 Sleep QUANTITY (Left panel): Younger Group: amnestic (p=0.003); non-amnestic (p=0.010) Older Group: amnestic (p=<0.001); non-amnestic (p<0.001) *Adjusted for: age, sex sleep*age, education, employment grade, depression, physical activity, smoking, general health. Miller et al., PLOS ONE 2014 (In press) Sleep QUALITY (Right panel): Younger group: No significant associations Older group: amnestic (p=<0.001); non-amnestic (p<0.001)

17. Cognitive function scores by sleep categories adjusted for sleep quality. 17 LEFT PANEL: Adjusted mean amnestic T Score Analysis of covariance (ANCOVA) for sleep quantity and/or sleep quality, for amnestic or non-amnestic scores, and in both younger (50-64yrs) and older (65-89yrs) age groups (PLOS ONE in press. RIGHT PANEL: Adjusted mean non-amnestic T Score

18. Limitations Cross-sectional - reverse causality Need for prospective studies Self-reported sleep Questionnaires have been validated against PSG (but not in older population) Large, representative older cohort Wealth of data on cognition and confounders 18 Strengths

19. Conclusions Different associations between sleep and cognition in younger and older adults –Sleep quality only associated with cognition in older adults Similar associations for amnestic and non-amnestic function Prospective studies to reveal relationship between sleep and changes in cognition with ageing 19

20. Acknowledgments Wingate Hayley Wright, Chen Ji, Francesco P. Cappuccio We thank the following organizations for supporting our Programme and, specifically the ESRC for this project (ES/K002910/1).

21. Sleep quantity and sleep quality. 21 Mean sleep quality score for each sleep quantity category (upper panel, S1A-S1B), and mean sleep quantity (hours) for each sleep quality tertile (lower panel, S1C-S1D), in younger and older age groups. All unadjusted ANOVAs p < 0.001; see figures for p values for multiple comparisons (Bonferroni-corrected).