S. Hardoon, P. Whincup, L. Lennon, S. Wannamethee, S. Capewell et al., How Much of the Recent Decline in the Incidence of Myocardial Infarction in British Men Can Be Explained by Changes in Cardiovascular Risk Factors?: Evidence From a Prospective Population-Based Study, Circulation, vol.117, issue.5, pp.598-604, 2008.
DOI : 10.1161/CIRCULATIONAHA.107.705947

D. Abegunde, C. Mathers, T. Adam, M. Ortegon, and K. Strong, The burden and costs of chronic diseases in low-income and middle-income countries, The Lancet, vol.370, issue.9603, pp.1929-1967, 2007.
DOI : 10.1016/S0140-6736(07)61696-1

S. Capewell, C. Morrison, and J. Mcmurray, Contribution of modern cardiovascular treatment and risk factor changes to the decline in coronary heart disease mortality in Scotland between 1975??and 1994, Heart, vol.81, issue.4, pp.380-386, 1975.
DOI : 10.1136/hrt.81.4.380

B. Unal, J. Critchley, and S. Capewell, Explaining the Decline in Coronary Heart Disease Mortality in England and Wales Between 1981 and 2000, Circulation, vol.109, issue.9, pp.1101-1108, 2000.
DOI : 10.1161/01.CIR.0000118498.35499.B2

F. Hu, M. Stampfer, J. Manson, F. Grodstein, G. Colditz et al., Trends in the Incidence of Coronary Heart Disease and Changes in Diet and Lifestyle in Women, New England Journal of Medicine, vol.343, issue.8, pp.530-537, 2000.
DOI : 10.1056/NEJM200008243430802

K. Kuulasmaa, H. Tunstall-pedoe, A. Dobson, S. Fortmann, S. Sans et al., Estimation of contribution of changes in classic risk factors to trends in coronary-event rates across the WHO MONICA Project populations, The Lancet, vol.355, issue.9205, pp.675-87, 2000.
DOI : 10.1016/S0140-6736(99)11180-2

H. Wijeysundera, M. Machado, F. Farahati, X. Wang, W. Witteman et al., Association of Temporal Trends in Risk Factors and Treatment Uptake With Coronary Heart Disease Mortality, 1994-2005, JAMA, vol.303, issue.18, pp.1841-1848, 1994.
DOI : 10.1001/jama.2010.580

M. Marmot and E. Brunner, Cohort Profile: The Whitehall II study, International Journal of Epidemiology, vol.34, issue.2, pp.251-257, 2005.
DOI : 10.1093/ije/dyh372

H. Tunstall-pedoe, K. Kuulasmaa, P. Amouyel, D. Arveiler, A. Rajakangas et al., Myocardial infarction and coronary deaths in the World Health Organization MONICA Project. Registration procedures, event rates, and case-fatality rates in 38 populations from 21 countries in four continents, Circulation, vol.90, issue.1, pp.583-612, 1994.
DOI : 10.1161/01.CIR.90.1.583

E. Brunner, M. Marmot, I. White, O. Brien, J. Etherington et al., Gender and employment grade differences in blood cholesterol, apolipoproteins and haemostatic factors in the Whitehall II study, Atherosclerosis, vol.102, issue.2, pp.195-207, 1993.
DOI : 10.1016/0021-9150(93)90162-N

E. Brunner, M. Marmot, K. Nanchahal, M. Shipley, S. Stansfeld et al., Social inequality in coronary risk: Central obesity and the metabolic syndrome. Evidence from the Whitehall II study, Diabetologia, vol.35, issue.Suppl IV, pp.1341-1350, 1997.
DOI : 10.1007/s001250050830

A. Singh-manoux, M. Hillsdon, E. Brunner, and M. Marmot, Effects of Physical Activity on Cognitive Functioning in Middle Age: Evidence From the Whitehall II Prospective Cohort Study, American Journal of Public Health, vol.95, issue.12, pp.2252-2260, 2005.
DOI : 10.2105/AJPH.2004.055574
URL : https://hal.archives-ouvertes.fr/inserm-01155214

A. Thiebaut and J. Benichou, Choice of time-scale in Cox's model analysis of epidemiologic cohort data: a simulation study, Statistics in Medicine, vol.6, issue.2, pp.3803-3823, 2004.
DOI : 10.1002/sim.2098

D. Schoenfeld, Partial residuals for the proportional hazards regression model, Biometrika, vol.69, issue.1, pp.239-280, 1982.
DOI : 10.1093/biomet/69.1.239

L. Freedman, B. Graubard, and A. Schatzkin, Statistical validation of intermediate endpoints for chronic diseases, Statistics in Medicine, vol.57, issue.2, pp.167-78, 1992.
DOI : 10.1002/sim.4780110204

B. Efron and R. J. Tibshirani, An Introduction to the Bootstrap, 1993.
DOI : 10.1007/978-1-4899-4541-9

F. Boutitie, F. Gueyffier, S. Pocock, and J. Boissel, Assessing treatment-time interaction in clinical trials with time to event data: a meta-analysis of hypertension trials, Statistics in Medicine, vol.17, issue.24, pp.2883-903, 1998.
DOI : 10.1002/(SICI)1097-0258(19981230)17:24<2883::AID-SIM900>3.0.CO;2-L

A. Dobson, H. Alexander, R. Heller, and D. Lloyd, How soon after quitting smoking does risk of heart attack decline?, Journal of Clinical Epidemiology, vol.44, issue.11, pp.1247-53, 1991.
DOI : 10.1016/0895-4356(91)90157-5

M. Law, N. Wald, and S. Thompson, By how much and how quickly does reduction in serum cholesterol concentration lower risk of ischaemic heart disease?, BMJ, vol.308, issue.6925, pp.367-72, 1994.
DOI : 10.1136/bmj.308.6925.367

C. Weinberg, Toward a Clearer Definition of Confounding, American Journal of Epidemiology, vol.137, issue.1, pp.1-8, 1993.
DOI : 10.1093/oxfordjournals.aje.a116591

S. Hardoon, P. Whincup, S. Wannamethee, L. Lennon, S. Capewell et al., Assessing the impact of medication use on trends in major coronary risk factors in older British men: a cohort study, European Journal of Cardiovascular Prevention & Rehabilitation, vol.50, issue.5, pp.502-510, 2010.
DOI : 10.1097/HJR.0b013e3283378865

R. Prentice, R. Langer, M. Stefanick, B. Howard, M. Pettinger et al., Combined Analysis of Women's Health Initiative Observational and Clinical Trial Data on Postmenopausal Hormone Treatment and Cardiovascular Disease, American Journal of Epidemiology, vol.163, issue.7
DOI : 10.1093/aje/kwj079

S. Hardoon, R. Morris, M. Thomas, S. Wannamethee, L. Lennon et al., Is the Recent Rise in Type 2 Diabetes Incidence From 1984 to 2007 Explained by the Trend in Increasing BMI?: Evidence from a prospective study of British men, Diabetes Care, vol.33, issue.7, pp.1494-1496, 2010.
DOI : 10.2337/dc09-2295

J. Non, 214) Effect of adjustment for combinations of risk factors K Smoking, non-HDL cholesterol, HDL cholesterol, systolic blood pressure 2

L. Smoking, systolic blood pressure, usual fruit and vegetable consumption 2

M. Smoking, systolic blood pressure, usual fruit and vegetable consumption, BMI 3