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Medically Reviewed By: Expert-24 Medical Review Board on March 27, 2014 | References

HEALTHTOOLS™ (HEALTHRISK™ AND HEALTHAGE™) DOES NOT PROVIDE MEDICAL ADVICE. It is intended for informational purposes only. It is not a substitute for professional medical advice, diagnosis or treatment. Never ignore professional medical advice in seeking treatment because of something you have read on the site. If you think you may have a medical emergency, immediately call your doctor or dial 911.

Expert Review Panel – Expert-24 Ltd

Terms of reference

The aim of the Expert Review Panel is to ensure that all Expert-24 clinical and epidemiological content is robust, independent and up to date.


Medical Director and Editor

Dr. Timothy Dudley

Chairman of the Expert Review Panel

Dr. Robin Christie

Current authors and reviewers for the Health Risk Assessment

Dr. Martin Dawes

Dr. Jonathan Mant

Emeritus authors and reviewers for the Health Risk Assessment

The following individuals were deeply involved in the creation of the health risk assessment at its inception, but are no longer active reviewers on the panel:

Dr. John Fletcher

Dr. Emma Boulton

Professor Larry Ramsay

Professor Klim McPherson

Patient-centered health risk using an Evidence Based Medicine approach

Who created it and how often is it reviewed and updated?

This health risk assessment is brought to you by Expert-24 Limited. Expert-24 Ltd has full editorial control over content and strives to ensure that the content is: 

  • Robust - All information used is derived from reputable, referenced sources and subject to rigorous expert review. The content is written by the medical staff of Expert-24 and reviewed by an independent Expert Review Panel. All content is subject to regular review and updated to incorporate the latest evidence. Oxford Health Consulting was commissioned to conduct independent research to determine the model for disease and mortality-specific risks, the contents and its assumptions. The research and statistical modeling behind the risk assessment has been led by Dr. John Fletcher. Dr. Fletcher is deputy editor of the Canadian Medical Association Journal. He holds a Masters degree in Public Health Quantitative Methods and is a member of the Royal College of General Practitioners. 
  • Independent - The content on the site is provided by Expert-24 Limited, an independent UK company providing knowledge automation and decision support tools to improve health and wellbeing. No member of the Expert Review Panel has any financial stake in Expert-24 Ltd. Content creation and ongoing Quality Assurance is provided by Expert-24 Ltd and its Expert Review Panel. 
  • Up to date - All clinical material is subject to review by Expert-24 and its Expert Review Panel at least annually.

Why is this health risk assessment different than others?

Most health risk assessments say if a person is at high, medium or low risk of either dying from or developing a given medical condition. Most also indicate what lifestyle factors contribute to this risk. What they do not say is the magnitude of each risk for an individual and how much that person’s risk will decrease if they change their lifestyle. For example, if one is at moderate risk of two diseases, say bowel cancer and heart disease, most people would be unaware that their risk of heart disease is still five times higher than their risk of bowel cancer. 

In order to construct an electronic risk assessment tool for health and disease states, it is necessary to provide supporting research evidence and a method of encapsulating the best estimate of relative risk. For each medical condition, it is necessary to present credible estimates of risk, based on evidence from relevant, peer reviewed medical research. Important features of the risk assessment tool are: 
  • The tool gives numerical estimates of risk, rather than an imprecise statement such as "increased risk" or "reduced risk". 
  • The tool has the capability for interaction, allowing users to explore the impact on their personal risk of changing individual risk factors. 
  • The tool utilizes best available medical evidence 

The aim of this project is to provide healthy people with a quantitative assessment of their personal risk of developing some important diseases and some of the factors that influence their risk. This is an ambitious task and we would not claim to have produced the definitive approach. Although we believe this is the most informative collection of disease prediction equations available at the present time they do have limitations. The ones we are aware of are outlined below.

What exactly does a given percentage risk mean?

Someone looking at their risk of lung cancer until the age of 50 should read this model as saying, "Assuming survival to age 50 the chance of developing lung cancer during that time would be (some predicted value)". This approach has the appeal that changing risk factors will have the expected impact on cumulative risk and the mathematics remains transparent. We chose the risk of developing a certain condition rather than the risk of dying from it because for many people the fear of living and dealing with a disabling disease is as frightening as dying from it. 

This is different than lifetime risk calculations, which generally calculate the risk of dying from a given condition. Lifetime risk must take account of the fact that we all die of something in the end and calculating the relative contribution of common competing causes of death at various ages is difficult. Not only that, but the interpretation by users is complex. For example, a user of an interactive model predicting lifetime risk of lung cancer would see their individual risk of lung cancer fall with increasing cigarette consumption, because they would be dying of heart disease and chronic lung disease before they could get lung cancer.

How accurate are these percentages?

These models are good for illustrating the change in risk due to the presence or absence of single risk factors for prediction times of up to 5 years. They are likely to be reasonably good for 15 or 20 years and for combinations of several risk factors. For longer prediction times and varying more than, say, four risk factors the results should be regarded as illustrative rather than precise. The absolute level of risk for an individual may also be wide of the mark because the majority of overall risk remains unexplained in most research studies. This is why "confidence intervals" have not been included. That said these prediction equations do calculate the best estimate of risk that can be provided on the data given. 

Is this useful in the end? We believe it is. We believe that putting some quantification on risk allows users to explore the possible impact on their health of altering what they do. We find this approach more informative than a bland statement of "high risk" that is often value laden or that a certain action will "cut down" a risk without any indication of by how much.

Is risk really reversible?

This is a difficult question to answer, but in many cases the answer seems to be, "yes". This is good news for people with high risks who are older. Intuition might tell you that you are constantly doing damage to your body that accumulates over time, and in many cases that may be true. An example of this is in skin cancer, where the earlier and more often you are badly burned in life, the higher your risk of skin cancer. Staying out of the sun when you are old cannot reverse this risk. 
However, there is good evidence that for heart disease, for example, your risks can be significantly reduced no matter what your age. Cholesterol reduction by medications called "statins" reduces the risk of heart attack, angina or sudden death from heart problems by up to 30%, and this is entirely independent of age. Similarly, blood pressure reduction by drugs reduces the risk of stroke and heart disease by 25% - again entirely independent of age. Because in general it is older people who have the highest risks, they actually stand to benefit the most from treatment. 

The risk for developing heart disease in tobacco users has been shown to decline to a level comparable with a person who has never smoked within 2-3 years of giving up. Furthermore, the risk of having a stroke is reversed after 5-10 years of stopping. Studies have also shown that life expectancy improves even in people who stop smoking later in life (i.e. at 65 years or older). 

The reduction of risk that can be obtained from changing lifestyle habits such as diet, alcohol consumption and exercise is largely unknown. Therefore, the amount of risk reduction that can be expected from optimizing these habits needs to be viewed with caution. Certainly they should not take the place of blood pressure control, cholesterol control, and smoking cessation as goals.

How good is the evidence?

Our aim in searching for evidence was to identify up to ten high quality, relevant research studies for each topic. We used Medline to search using free text, MeSH terms and thesaurus search terms specific to each medical condition. To narrow the documents we used filters using "risk" and study design type; cohorts, case control, longitudinal, follow up. Searches were limited to studies published in English language and human studies. Although a comprehensive systematic review of the literature on each disease was not possible due to the scope of this project, we feel that the evidence used represents a reasonable cross-section of high-quality literature on the subjects in question. 
What we have done is to seek out plausible values of relative risk to use in the prediction equations. We have used an approach that searches for high quality research studies and have then applied our judgment tempered by Austin Bradford Hill's criteria for causation when selecting which risks to use. Hill's criteria are: strength, consistency, specificity, temporality, biological gradient, plausibility, coherence, experimental evidence and analogy. 

If this sometimes appears somewhat subjective then that is because at times it is a matter of judgment. The judgments have seldom altered the relative risk by more than a small amount. For each risk factor we had to choose a value to use in the model and have been faced at times with a range from which to choose. While a meta-analysis may provide the best point estimate, one is not always available and would be spurious to conduct on the sample of studies we have used for each condition. Given the level of uncertainty surrounding an individual's absolute personal risk we are comfortable with a comparatively lesser degree of uncertainty regarding a risk factor's relative risk.

What is the mathematical model that is used?

The actual mathematical and statistical models and risk coefficients that are used to determine risk are proprietary at this time, but have been validated by the authors and reviewers to be appropriate for use in this setting. 

References: Health Age Calculator

Most recently reviewed:

  1. Kvaavih E, et al. Influence of Individual and Combined Health Behaviors on Total and Cause-Specific Mortality in Men and Women. The United Kingdom Health and Lifestyle Survey. Arch Intern Med 2010; 170 (8): 711-718
  2. Pan A, et al. Red Meat Consumption and Mortality. Results from 2 prospective cohort studies. Arch. Int. Med. Published online March 12, 2012.
  3. Dunstan DW et al. Television Viewing Time and Mortality: The Australian Diabetes, Obesity and Lifestyle Study. Circulation 2010; 121: 384-391

Selected articles from previous reviews:

  1. Mitrou PN, Kipnis V, Thiébaut ACM, et al. Mediterranean Dietary Pattern and Prediction of All-Cause Mortality in a US Population: Results From the NIH-AARP Diet and Health Study. Archives of Internal Medicine. 2007;167(22):2461-8.
  2. Sofi F, Cesari F, Abbate R, et al. Adherence to Mediterranean diet and health status: meta-analysis. British Medical Journal. 2008;337:a1344-50.
  3. White, IR, Altmann, DR, Nanchahal, K. Alcohol consumption and mortality: modeling risks for men and women at different ages. BMJ 2002 Vol 325: 191
  4. Gaziano, JM et al. Light to Moderate Alcohol Consumption and Mortality in the Physician’s Health Study Enrollment Cohort. J Am Coll. Card. 2000: Vol 35. No 1.
  5. Thun, MJ et al. Alcohol consumption and Mortality among Middle-Aged and Elderly US Adults. NEJM 1997; 337: 1705-1714
  6. Khaw, KT, et al. Combined Impact of Health Behaviours and Mortality in Men and Women: The EPIC Norfolk Prosepctive Population Study. PLoS
  7. Med 5(1): e12. doi:10.1371/journal.pmed.0050012 (January 8, 2008)
  8. Benetou, V. et al. Conformity to traditional Mediterranean diet and cancer incidence: Greek EPIC cohort. British J. Ca. (1 July, 2008) 99, 191-195
  9. Kushi, L.H. et al. American Cancer Society Guidelines on Nutrition and Physical Activity for Cancer Prevention: Reducing the Risk of Cancer With Healthy Food Choices and Physical Activity CA Cancer J. Clin. 2006; 56 (5):254-281
  10. Chlebowski RT, et al. Dietary fat reduction and breast cancer outcome: interim efficacy results from the Women's Intervention Nutrition Study. J Natl Cancer Inst. 2006 Dec 20;98(24):1767-76.
  11. Michels, K.B., "A prospective study of variety of healthy foods and mortality in women." Int J Epidemiol 01 Aug 2002; 31(4): 847-54.
  12. Katzmarzyk, P.T., "Adiposity, adipose tissue distribution and mortality rates in the Canada Fitness Survey follow-up study." Int J Obes Relat Metab Disord 01 Aug 2002; 26(8): 1054-9.
  13. Andersen, L.B., "All-cause mortality associated with physical activity during leisure time, work, sports, and cycling to work." Arch Intern Med 12 Jun 2000; 160(11): 1621-8
  14. Prescott, E., "Importance of light smoking and inhalation habits on risk of myocardial infarction and all cause mortality. A 22 year follow up of 12 149 men and women in The Copenhagen City Heart Study." J Epidemiol Community Health 01 Sep 2002; 56(9): 702-6
  15. Fraser, G.E., "Association among health habits, risk factors, and all-cause mortality in a black California population.", Epidemiology, Mar 1997; 8 (2): 168-74.
  16. Tilling, K., "Estimating the effect of cardiovascular risk factors on all-cause mortality and incidence of coronary heart disease using G-estimation: the atherosclerosis risk in communities study." American Journal of Epidemiology 15 Apr 2002; 155(8): 710-8
  17. Yuan et al, "Follow up study of moderate alcohol intake and mortality among middle-aged men in Shanghai, China", BMJ 1997 314:18-23
  18. Fuchs et al, "Alcohol consumption and mortality amongst women", NEJM 1995 332:1245-1250
  19. Wannamethee et al, "Lifelong teetotallers, Ex drinkers and Drinkers: Mortality and the incidence of major coronary heart disease events in middle aged British men", International Journal of Epidemiology 1997 26:523-531
  20. Thun et al, "Alcohol consumption and mortality among middle aged and elderly US adults", NEJM 1997 337:1705-1713
  21. Hart et al, "Alcohol consumption and mortality from all causes, coronary heart disease and stroke: results from a prospective cohort study of Scottish men with 21 yrs follow up", BMJ 1999:318:1725-9
  22. "Diabetes mellitus, coronary heart disease incidence and death from all causes in African American and European American women". The NHANES I epidemiologic follow up study
  23. Lotufo et al , "Diabetes and all cause and coronary heart disease mortality among US male physicians", Arch Intern Med 2001; 161:242-7
  24. Lotufo et al, "Diabetes and all cause and coronary heart disease mortality among US male physicians", Arch Intern Med 2001; 161:242-7
  25. Stamler et al, "Relationship of baseline serum cholesterol levels in 3 large cohorts of younger men to long term coronary, cardiovascular and all cause mortality and to longevity", JAMA 2000;284:311-8
  26. Doll and Peto, "Mortality and relation to smoking: 20 yrs observations on male British Doctors", BMJ 1976: 2:1525-1536
  27. Doll et al, "Mortality in relation to smoking:22 years observations on female British doctors", BMJ 5/4/80 p 967-971
  28. Jacobs et al, "Cigarette smoking and mortality risk. Twenty five year follow up of the seven countries study", Arch Intern Med 1999; 159:733-40
  29. I Min Lee et al, "Body weight and mortality, a 27 yr follow up of middle-aged men", JAMA 1993;270:2823-8
  30. Blair et al, "Body weight change, all cause mortality in the multiple risk factor intervention trial", Ann Intern Med 1993;119:749-57
  31. Seidell et al, "Overweight, underweight and mortality. A prospective study of 48287 men and women", Arch Intern Med. 1996;156:958-63
  32. Manson et al, "Body weight and mortality among women", NEJM 1995; 333:677-85
  33. Colditz et al, "Oral contraceptive use and mortality during 12 years of follow up: The Nurses Health Study", Ann Intern Med. 1994;120:821-6
  34. Morris et al, "Loss of employment and mortality", BMJ 1994; 308:1135-9
  35. Martikainen et al, "Income differences in mortality: a register based follow up study of three million men and women", Int Journal of Epidemiology 2001; 30:1397-1405)
  36. Matthews et al, "Chronic work stress and marital dissolution increase risk of post-trial mortality in men from the MRFIT", Arch Intern Med. 2002;162:309-15
  37. Ben Schlomo et al, "Magnitude and causes of mortality differences between married and unmarried men", J Epidemiol Community Health 1993;47:200-5
  38. Kawachi et al, "A prospective study of social networks in relation to total mortality and cardiovascular disease in men in the USA", J Epidemiology and Community Health 1996;50:245-251
  39. "The diet and all cause death rate in the Seven Countries Study", The Lancet July 11, 1981;58-61
  40. Huovinen et al, "Mortality of adults with asthma; a prospective cohort study", Thorax 1997; 52:49-54
  41. Johansen et al, "Important risk factors for death in adults: a 10 yr follow up of the Nutrition Canada survey cohort", CMAJ 136:823-8
  42. Knuiman et al, "Lung function, respiratory symptoms, and mortality. Results from the Busselton Health Study", Ann Epidemiol 1999;9:297-306
  43. Dockery et al, "An association between air pollution and mortality in six US cities", NEJM 1993;329:1753-9
  44. Wannamethee S.G. et al, "Lifestyle and 15 year survival free of heart attack, stroke and diabetes in middle aged British Men", Archives of Internal Medicine 1998:158; 2433-2440
  45. Strandberg T.E. et al, "Blood pressure and mortality during an up to 32 year follow up", Journal of Hypertension 2001:19;35-39.
  46. Haapanen N. et al, "Characteristics of leisure time physical activity associated with decreased risk of premature all cause and cardiovascular disease mortality in middle aged men", American Journal of Epidemiology, 1996:143;870-80.
  47. Keil U., et al, "Classical risk factors and their impact on incident non-fatal and fatal myocardial infarction and all cause mortality in southern Germany (MONICA Augsburg cohort)", The European Heart Journal 1998:19;1197-1207.