1. Effect of adult life course blood pressure on cardiac structure in the MRC 1946 birth cohort British Hypertension Society 2011 Dr Arjun K Ghosh MRC Clinical Career Development Fellow and Specialty Registrar in Cardiology, International Centre for Circulatory Health, Imperial College, London

2.  MRC NSHD is the oldest British birth cohort study  5362 men and women born in one week in March 1946  >20 data collection time-points throughout life  1653 echocardiograms at most recent data collection (age 60-64y)  Life course approach to data analysis Background

3. Life course approach  Hypothesis: exposures acting over the life course affect disease susceptibility  e.g. BP across the life course has an effect on subsequent left ventricular (LV) structure  The life course approach may offer better mechanistic understanding and allow earlier targeted interventions Mean SBP changes in 1946 cohort 110 115 120 125 130 135 140 145 305070 SBP (mmHg) Age (years) SBP MenSBP Women

4.  To examine the effects of adult life course systolic blood pressure (SBP) on future LV structure (LV wall thickness and mass)  To determine if previous SBPs can add anything over and above current SBP as a predictor of future LV wall thickness and mass  To determine if rate of change in SBP or “cumulative burden” of SBP influences future LV structure  To investigate the effect of antihypertensive treatment over the life course on LV structure Aim

5.  Series of multivariable regression models fitted with cardiac outcome (all models adjusted for sex)  Sex by SBP interactions tested in order to investigate if associations differ in men and women  Order of modelling: i.SBP from each round fitted separately ii.SBP from 2 rounds of data collection iii.Treatment for hypertension included in addition to SBP iv.Examined whether change in SBP from 36y to current age or “cumulative burden” of SBP [represented by Area Under the Curve (AUC) of SBP] predict current LV wall thickness and mass Methods

6. Results – predictive value of previous SBP on LVMI Regression coefficients (g / cm 2 per mm HG), 95% confidence intervals and p values for 4 separate sex-adjusted models containing SBP at different ages and current LV mass index (LVMI) Variable  coefficient (95% CI )p value SBP (current)0.20(0.12 to 0.27)<0.001 SBP (age 53)0.28(0.21 to 0.35)<0.001 SBP (age 43)0.13(0.04 to 0.22)0.007 SBP (age 36)0.14(0.04 to 0.24)0.006

7. Results – predictive value of previous SBP over and above current SBP on LVMI Regression coefficients (g/cm 2 per mm HG), 95% confidence intervals, p values and adjusted r 2 for predictors of LVMI in a sex-adjusted multivariable model containing both current SBP and SBP at age 53 Variable  coefficient (95% CI )p valuer2r2 SBP (current) 0.08 (0.002 to 0.16)0.046 0.13 SBP (age 53) 0.25(0.18 to 0.33)<0.001

8. Results – Effect of treatment on LVMI Regression coefficients (g/cm 2 treatment vs. no treatment), 95% confidence intervals and p values for 4 separate sex-adjusted models with treatment and SBP at different ages and current LVMI Variable  coefficient (95% CI )p value Current Rx12.3(9.2 to 15.4)<0.001 Rx at age 5310.0(5.9 to 14.1)<0.001 Rx at age 4315.1(5.8 to 24.3)0.001 Rx at age 36- 0.6(-14.7 to 13.6)0.939

9. Rate of change vs. Area Under the Curve AUC and slopes for two individuals – one with persistently elevated SBP, the other with gradually increasing SBP

10. Results – Rate of change of SBP from age 36y to 53y on LVMI Regression coefficients (g/cm 2 per mm HG/ year; g/cm 2 per mm HG), 95% confidence intervals, p values and adjusted r 2 for a sex-adjusted model with change in SBP (36-53y), SBP at 36y, current SBP and current LVMI Variable  coefficient (95% CI )p valuer2r2 Rate of change in SBP from 36 to 53y 18.4 (11.7 to 25.1) <0.001 0.13 SBP at 36y 0.2 (-0.0 to 0.4) 0.12 Current SBP 0.1 (0.0 to 0.2) 0.02 Two components in calculating the Area Under the Curve

11.  SBP over the adult life course predicts future LV structure  SBP at age 53 is a stronger predictor of LVMI than current SBP, although both independently predict LVMI in a multivariable model  Rate of change in SBP from 36y to 53y may be an important determinant of future LV structure  Antihypertensive treatment from the age of 43 onwards is associated with elevated LVMI independent of SBP at the corresponding age, suggesting that treatment may fail to normalize LVMI  A chance to intervene missed? Conclusions

12.  My Supervisors, funders and mentor – Professor Alun Hughes, Dr Rebecca Hardy, Dr Darrel Francis, Professor Nishi Chaturvedi, Professor Di Kuh and Professor Jamil Mayet  Colleagues at MRC LHA  Colleagues at ICCH, Imperial College Acknowledgements

13. Thank You

14.  Mean BP 136/78  Mean BP in men 140/80, mean BP in women 133/76  Mean BP in those on antihypertensive treatment 139/79  Mean BP in those off antihypertensive treatment 135/77  Mean BMI 27.94, similar in men and women BP and BMI characteristics

15.  Age 36 – 51  Age 43 – 107  Age 53 – 438  Age 60-64 - 640 Number of people on antihypertensive treatment