1 / 28

Healthy Ageing across the Life Course: Findings from the HALCyon Collaborative Research Programme

Healthy Ageing across the Life Course: Findings from the HALCyon Collaborative Research Programme Rachel Cooper on behalf of Diana Kuh and the HALCyon study team November 2010 GSA’s 63 rd Annual Scientific Meeting, New Orleans. HALCyon study team.

zasha
Download Presentation

Healthy Ageing across the Life Course: Findings from the HALCyon Collaborative Research Programme

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Healthy Ageing across the Life Course: Findings from the HALCyon Collaborative Research Programme Rachel Cooper on behalf of Diana Kuh and the HALCyon study team November 2010 GSA’s 63rd Annual Scientific Meeting, New Orleans

  2. HALCyon study team Diana Kuh, Avan Aihie Sayer, Yoav Ben-Shlomo, Ian Day, Ian Deary, Jane Elliott, Catharine Gale, James Goodwin, Rebecca Hardy, Alison Lennox, Marcus Richards, Thomas von Zglinicki, Cyrus Cooper, Panos Demakakos, John Gallacher, Richard Martin, Gita Mishra, Chris Power, Paul Shiels, Humphrey Southall, John Starr, Andrew Steptoe, Kate Tilling, Geraldine McNeill, Leone Craig, Carmen Martin-Ruiz, Scott Hofer Tamuno Alfred, Paula Aucott, Sean Clouston, Rachel Cooper, Mike Gardner, Emily Murray, Zeinab Mulla, Sam Parsons, Vicky Tsipouri plus a Knowledge Transfer Steering Group and 19 national and international collaborators

  3. What is HALCyon? A collaborative research programme: • 9 UK cohorts born early 1900’s to 1958 • 27 investigators, 8 doctoral and post-doctoral researchers, 19 collaborators • Core project + 8 work packages • Funded from Sept 2008 – March 2012 Aim: to improve the lives of older people by understanding how healthy ageing is influenced by factors operating across the whole of life

  4. What is being studied? Indicators of healthy ageing: • Capability: the capacity to undertake the physical and mental tasks of daily living • Wellbeing: psychological and social • Underlying biology: physiology and genetics

  5. 8 integrated work packages

  6. 9 HALCyon cohorts

  7. Analytical strategy • Systematic review and possibly meta-analysis • Across HALCyon cohorts – data harmonisation, consistent analysis and investigation of confounding variables • In depth analysis in relevant specific cohorts to answer particular life course questions In depth analysis Cross cohort Systematic review

  8. Physical capability measures in the HALCyon cohorts

  9. Physical capability • Are objective measures of PC useful markers of ageing? • What are the age and gender differences in PC? • Do childhood socioeconomic circumstances influence PC levels in adulthood? • How are body size and PC associated? • Does the area in which a person lives influence their PC? • Do specific genetic variants influence PC?

  10. Study author/s (sex) (Total N (no. of deaths)) HR (95% CI) HR (95% CI) Al Snih (B) (N=2488 (507)) 0.96 (0.95, 0.97) 0.96 (0.95, 0.97) Cawthon & Ensrud (M)(MrOS) (N=5631 (1070)) 0.96 (0.95, 0.97) 0.96 (0.95, 0.97) Cawthon & Ensrud (F)(SOF) (N=9700 (5536)) 0.97 (0.96, 0.98) 0.97 (0.96, 0.98) Cesari 2008* (B) (N=335 (71)) 0.98 (0.96, 1.00) 0.98 (0.96, 1.00) Gale (B) (N=800 (756)) 0.99 (0.98, 1.00) 0.99 (0.98, 1.00) Katzmarzyk (B) (N=8148 (269)) 0.98 (0.96, 1.00) 0.98 (0.96, 1.00) Klein (B) (N=2612 (194)) 0.95 (0.93, 0.97) 0.95 (0.93, 0.97) Newman* (B) (N=2292 (286)) 0.97 (0.95, 0.99) 0.97 (0.95, 0.99) Rantanen (M) (N=6040 (2900)) 0.97 (0.96, 0.98) 0.97 (0.96, 0.98) Sasaki (B) (N=4821 (2407)) 0.98 (0.97, 0.98) 0.98 (0.97, 0.98) Shibata* (M) (N=192 (59)) 1.00 (0.99, 1.01) 1.00 (0.99, 1.01) Shibata* (F) (N=221 (43)) 0.99 (0.96, 1.02) 0.99 (0.96, 1.02) Syddall (B) (N=714 (52)) 0.95 (0.91, 0.99) 0.95 (0.91, 0.99) Takata* (B) (N=642 (94)) 0.97 (0.93, 1.02) 0.97 (0.93, 1.02) Overall (I-squared = 89.5%, p < 0.001) 0.97 (0.96, 0.98) 0.97 (0.96, 0.98) .911 1 1 1.1 Hazards ratio per 1kg increase in grip strength Hazards ratios of mortality per 1 kg increase in grip strength Adjusted for age, sex, body size (or *multiple factors)

  11. BMJ 2010;341:c4467 Age and Ageing 2010 10.1093/ageing/afq117 

  12. Physical capability • Are objective measures of PC useful markers of ageing? • What are the age and gender differences in PC? • Do childhood socioeconomic circumstances influence PC levels in adulthood? • How are body size and PC associated? • Does the area in which a person lives influence their PC? • Do specific genetic variants influence PC?

  13. Differences in grip strength by age and gender Cooper et al, in preparation

  14. Physical capability • Are objective measures of PC useful markers of ageing? • What are the age and gender differences in PC? • Do childhood socioeconomic circumstances influence PC levels in adulthood? • How are body size and PC associated? • Does the area in which a person lives influence their PC? • Do specific genetic variants influence PC?

  15. Study Sex Mean age (y) Regression coefficient (95% CI) Father's occupation Lothian Birth Cohort 1921 M 79 -0.26 (-0.47, -0.05) F -0.24 (-0.38, -0.10) Hertfordshire Ageing Study M 76 -0.06 (-0.16, 0.04) F -0.01 (-0.14, 0.12) Health and Retirement M 75 -0.13 (-0.18, -0.09) F -0.14 (-0.18, -0.10) Caerphilly Study M 73 -0.06 (-0.09, -0.03) PREHCO project M 72 0.05 (-0.03, 0.12) F 0.01 (-0.05, 0.08) Boyd Orr M 71 -0.03 (-0.11, 0.05) F -0.04 (-0.11, 0.03) Lothian Birth Cohort 1936 M 69 -0.12 (-0.26, 0.02) F -0.13 (-0.24, -0.02) Hertfordshire Cohort Study M 68 -0.06 (-0.09, -0.03) F -0.04 (-0.11, 0.03) ELSA M 66 -0.16 (-0.20, -0.12) F -0.12 (-0.16, -0.08) Aberdeen 1936 M 65 -0.04 (-0.15, 0.07) F -0.13 (-0.22, -0.04) Overall (I-squared = 72.3%, p < 0.01) -0.08 (-0.11, -0.05) -.4 -.2 0 .2 Lower SEP=Worse function Better function Difference in mean walking speed (m/s) comparing lowest with highest SEP Childhood SEP and walking speed Adjusted for age Birnie, Cooper et al, in press

  16. Physical capability • Are objective measures of PC useful markers of ageing? • What are the age and gender differences in PC? • Do childhood socioeconomic circumstances influence PC levels in adulthood? • How are body size and PC associated? • Does the area in which a person lives influence their PC? • Do specific genetic variants influence PC?

  17. Current BMI Height Study reg. Study reg. coeff. (95% CI) coeff. (95% CI) Male Male LBC21 0.00 (-0.00, 0.01) 0.00 (-0.00, 0.01) LBC21 -0.02 (-0.03, -0.00) -0.02 (-0.03, -0.00) HAS 0.00 (-0.00, 0.00) 0.00 (-0.00, 0.00) HAS -0.01 (-0.02, -0.01) -0.01 (-0.02, -0.01) CaPs -0.00 (-0.00, 0.00) -0.00 (-0.00, 0.00) CaPs -0.01 (-0.01, -0.01) -0.01 (-0.01, -0.01) Boyd Orr 0.00 (0.00, 0.01) 0.00 (0.00, 0.01) Boyd Orr -0.01 (-0.01, -0.00) -0.01 (-0.01, -0.00) HCS 0.00 (0.00, 0.00) 0.00 (0.00, 0.00) HCS -0.01 (-0.01, -0.00) -0.01 (-0.01, -0.00) ELSA 0.01 (0.00, 0.01) 0.01 (0.00, 0.01) ELSA -0.01 (-0.01, -0.01) -0.01 (-0.01, -0.01) ABC36 0.01 (0.00, 0.01) 0.01 (0.00, 0.01) ABC36 -0.01 (-0.02, -0.00) -0.01 (-0.02, -0.00) (I-squared = 69.2%, p < 0.01) 0.00 (0.00, 0.00) 0.00 (0.00, 0.00) (I-squared = 14.5%, p = 0.32) -0.01 (-0.01, -0.01) -0.01 (-0.01, -0.01) Female Female LBC21 0.00 (-0.00, 0.01) 0.00 (-0.00, 0.01) LBC21 -0.02 (-0.03, -0.01) -0.02 (-0.03, -0.01) HAS 0.00 (-0.00, 0.01) 0.00 (-0.00, 0.01) HAS -0.01 (-0.01, -0.00) -0.01 (-0.01, -0.00) Boyd Orr 0.00 (-0.00, 0.00) 0.00 (-0.00, 0.00) Boyd Orr -0.01 (-0.01, -0.01) -0.01 (-0.01, -0.01) HCS -0.00 (-0.00, 0.00) -0.00 (-0.00, 0.00) HCS -0.01 (-0.01, -0.00) -0.01 (-0.01, -0.00) ELSA 0.01 (0.00, 0.01) 0.01 (0.00, 0.01) ELSA -0.01 (-0.01, -0.01) -0.01 (-0.01, -0.01) ABC36 0.01 (0.00, 0.01) 0.01 (0.00, 0.01) ABC36 -0.01 (-0.01, -0.00) -0.01 (-0.01, -0.00) (I-squared = 67.5%, p < 0.01) 0.00 (0.00, 0.01) 0.00 (0.00, 0.01) (I-squared = 53.7%, p = 0.06) -0.01 (-0.01, -0.01) -0.01 (-0.01, -0.01) (I-squared = 65.9%, p < 0.01) 0.00 (0.00, 0.00) 0.00 (0.00, 0.00) (I-squared = 47.4%, p = 0.03) -0.01 (-0.01, -0.01) -0.01 (-0.01, -0.01) -.04 -.02 0 0 .02 .04 -.04 -.02 0 0 .02 .04 poorer function better function poorer function better function Current BMI, height and walking speed (m/s) Hardy et al, in preparation

  18. Body size across life and physical capability Age

  19. Body size across life and physical capability Age

  20. Physical capability • Are objective measures of PC useful markers of ageing? • What are the age and gender differences in PC? • Do childhood socioeconomic circumstances influence PC levels in adulthood? • How are body size and PC associated? • Does the area in which a person lives influence their PC? • Do specific genetic variants influence PC?

  21. Data on area from across life in NSHD Childhood N=4,698 Young adulthood N=3,543 Mid-life N=2,955 Geocoded all Years N=2634 Physical capability 53 years N=2440 1950 1972 1999 Birth 4 8 11 15 26 43 5360+ Murray et al, in preparation

  22. Mean differences in balance time (log seconds) at age 53y by tertiles of area % unemployment at ages 26y and 53y in NSHD % unemployment 1972 : Low: 0.0 – 1.7, Med: 1.8 - 2.4, High: 2.4 – 6.8 1999: Low: 0.0 – 3.6, Med: 3.7 – 5.1, High: 5.2 – 11.2 1972 1999 Murray et al, in preparation http://www.seniorsworldchronicle.com/2007_10_07_archive.html

  23. Physical capability • Are objective measures of PC useful markers of ageing? • What are the age and gender differences in PC? • Do childhood socioeconomic circumstances influence PC levels in adulthood? • How are body size and PC associated? • Does the area in which a person lives influence their PC? • Do specific genetic variants influence PC?

  24. Association between TERT SNP rs401681 and poor balance Alfred et al, under review

  25. What we’ve learnt • Compiling and harmonising data from multiple cohorts is challenging and takes a long time but…. • Results provide empirical evidence that is often more robust than that from an individual study • Inter-cohort work should be used to complement more in-depth work conducted within individual studies Physical capability levels: • predict survival and subsequent morbidity • differ by gender and decline with age across UK cohorts • are influenced by childhood socioeconomic circumstances • vary by body size and neighbourhood characteristics

  26. Cognitive capability Inter-relationships between cognitive and physical capability Lifetime nutrition and capability Social and psychological wellbeing Qualitative study - Comparisons between cohorts on the meaning & experience of ageing HPA axis and cortisol levels Telomere length - repeat measures on large sample sizes - interlab comparisons Other ongoing and future work

  27. www.halcyon.ac.uk

  28. Acknowledgements The HALCyon study team Diana Kuh, Tamuno Alfred, Kate Birnie, Rebecca Hardy and Emily Murray New Dynamics of Ageing and UK Medical Research Council Contact: r.cooper@nshd.mrc.ac.uk

More Related