Sunday, August 15, 2010


Overweight and obese people are generally thought to be unhealthy and have more diseases and higher death rate than people of normal weight. However, such information is usually found in articles written by authors who have not examined the actual medical evidence which support these statements. The purpose of this paper is to take a close look at the evidence for some of these claims.

There is no agreement among epidemiologists concerning the increased risk of death in overweight and obese individuals. Some studies indicate that no relationship exist and some that the relationship is the reverse. Some studies agree that obese people are more likely to die than people of normal weight, but there is disagreement concerning overweight people and increased risk of death. Some say yes and others say no. These studies have been summarized by McGee (2005) who concluded that overweight people do not have a significantly higher rate of death than normal weight people.

A recent study claims that even overweight women or men are at a greater risk of dieing than people of normal weight (Adams et al 2006). In their study the relative and actual risks were elevated for under weight, obese men and surprisingly men and women in the normal weight categories 2 and 3 (Table 1). These conclusions are taken from relative risk ratio statistics in column 2. In this table I have added the relative risk as percent (column 3) and the actual risk as percent (column 4) for comparison. It is apparent that the actual risk of death is not great even for obese men in which the increase is only 1.9% greater than the normal reference body weight of 1.3%. Underweight men have an elevated actual risk (3.5%) which is similar to those who are overweight (3.2%). Similar risks were found for all women studied (results not shown).


*Similar results were found for women. **BMI or Body Mass Index is
equal to the body weight in kg divided by height in meters squared.

A BMI calculator can be found at

The conclusions that can be drawn from Table 1 are:

1. Underweight and some low normal weight individuals are at an increased risk of death. This important point rarely gets a mention in the news media or fashion magazines.

2. Overweight people are not at an elevated risk of death.

3. Obese people have an elevated risk of death similar to underweight individuals.


In order to examine the effect of bodyweight on risk of death the influence of smoking was considered by Adams et al (2006). To do this data were grouped into the following groups: Never Smoked, Current Smoker and Former Smoker. For the sake of simplicity I have made a table which shows data from never smokers and current smokers (Table 2).


* Actual risk was calculated by dividing the number of individual in each category by 100,000. Data were obtained from table 2 in Adams et al (2006).

If you look only at the results of relative risks and compare never smokers with current smokers you could draw the incorrect conclusions that it is better to be an obese smoker than an obese non-smoker. For example, in group 10 the relative risk for the never smoker is 159%, whereas for the current smoker in this group the risk is 42%. This is a good example of how relative risks can be misleading and why actual risks should be used in these kinds of studies. Comparing the actual risks in these two groups provides the correct answers. The actual risk of death in category 10 for the never smoker group is 2.6% compared to 5.0% for the current smoker group. So just as we suspected being obese and smoking is not good for you.

The reason for the reversal seen with relative risk analysis is that the reference category 4 is a lower number (0.78) in the never smoker group than that of the current smoker group (3.08). Since all weight categories are compared to these numbers the relative risk increases in the smoker groups are lower. For example: in the never smoker group the percent in category 10 is 2.6 compared to 0.78 in the reference group. Therefore the relative risk is 3.25 times as great as the reference value of 0,78 for never smokers and only 1.61 times as great for current smokers (5.0/3.08 = 1.61).

The influence of smoking on the actual risk of death is shown in figure 1. It is clear from these data that current smoking increases the actual risk of death in all BMI categories. The data for women are similar to men (data not shown). In this figure and in table 2 we see that men in the never smoked group show similar actual risks in all categories except the obese groups 9 and 10 and these are not great but they were judged to be significant by Adams et al (2006). The former smokers have a small actual increase in risk in categories 3 – 8 and elevated risks in the underweight, low normal and obese categories. There is no evidence from these data that being overweight increased your risk of death.

Figure 1 Actual risk of death as function of BMI groups in smokers and non-smokers.


My conclusion that being overweight does not increase the risk of death agrees with that of McGee (2005) who analyzed 26 large population studies which included 388,622 individuals.


Data taken form McGee 2005. The data are expressed as relative risks and the 95% confidence interval in parentheses. All groups were compared to normal weight individual defined as having a BMI of 18.5 to 25. Over weight defined as BMI between 25 and 30 and obese as BMI of 30 or greater. Abbreviations: CHD, coronary heart disease; CVD, cardiovascular disease.

From table 3 it is clear that even the relative risks of death for overweight individuals is not different from those of normal weight. Actual risks could not be calculated because insufficient data. These data suggest that obese men and women are at a greater risk of death from all causes, CHD and CVD but not cancer. The lack of any increased risk of cancer in overweight women supports my contention that heavier women do not have higher risk of breast cancer.


1. Underweight and some low normal weight individuals are at an increased risk of death.

2. Overweight people are not at an elevated risk of death.

3. Obese people have an elevated risk of death similar to underweight individuals.

4. Current smoking in obese and under weight individuals increases their risk of death. This is also true for those in the former and never smokers but the risks are not as great.

5. Obesity increases the risk death from heart and vascular diseases but not cancer.

The finding that overweight men and women show no significant increased risk for heart and vascular diseases or death casts doubt on the continual bombardment from the news media, nutrition experts, many physicians, drug companies and food manufactures that being over weight will increase the incidence of many diseases.


McGee DL (2005) Ann Epidemiol 15:87

Adams KF (2006) N Engl J Med 355:763

Saturday, August 14, 2010



For the past few years nutritionist and epidemiologist have been having trouble demonstrating that dietary saturated fats and cholesterol increase the risk of coronary heart disease (CHD). However they kept their noses to the grind stone and have settled on trans fats as the culprit. Trans fats are semi-solid fats which result from the conversion of liquid oils into their partially hydrogenated forms. They are present in most of the good things you eat, everything from donuts to milk. The Food and Drug Administration has gone along with this most recent fat fad and decided that food labels must state the amount of trans fats in all products. The Department of Agriculture has made a key recommendation that trans fat intake should be limited in their new food pyramid guidelines. Several other actions have been taken by various governmental agencies at home and abroad to limit or eliminate trans fats from our diets.

My question is: are trans fats all that bad and is worth the time, money and trouble to take them out of foods. I seem to remember when these same agencies were trying to limit saturated fat and cholesterol in our diets. Actually they still are because they are not able to face the facts that dietary saturated fat and cholesterol do not increase risk of heart disease.


The more important papers in the past 10 years concerned the supposed dangers of trans fats can be found in a review article written by Mozaffarian et al (1). It was important because it was picked up by the news media and given the appropriate level of hype. But, as I have asked before, did anyone in the news media or anywhere else actually read this paper? Well I did and here is my summary of it and the studies it uses to suggest that trans fats are bad. I will also review a couple of others along the way.

For each of the studies I will provide a brief summary for the readers who doesn’t want to cloud their mind with all of the statistical based arguments.


Study 1. Mozaffarian et al (1).

The data in this review article clearly shows no association between dietary saturated fat or cholesterol and the incidence of heart disease. They also provide data which indicates a slight increase in risk of heart disease ( relative risk: 40%, actual risk: 0.12%). This very low increase becomes insignificant when amount of fiber in the diet is taken into account. It seems that people who eat the most trans fats also have the lowest quantity of fiber in their diets. This is obviously related to the attitude: that French fries are better than broccoli any day. So it’s the lack of fiber that is dangerous, not the intake of trans fats.

Study 2. Nurse’s Health Study by Oh et et al (4).

These authors demonstrate in agreement with other studies that dietary total fat, saturated fat and unsaturated fat do not increase the risk of heart disease; however, they do try to implicate trans fat. Their story is poor because the data on estimated risks are only slightly different from no effect. There is no indication that they corrected the data for fiber intake which would reduce any elevated risk even more, so my judgment is the data are too weak to show any actual differences.

Study 3. Zutphen Elderly Study by Oomen et al (5).

Another study which shows a marginal increased risk of heart disease associated with dietary trans fat intake. Too little data and too close to call.

4. The Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study by Pietinen et al (6).

One more study which shows no increased risk of heart disease associated with dietary saturated fat, cholesterol, monounsaturated fats, total triglycerides and saturated fatty acids. Dietary trans fat was not associated with an increase in heart disease but it was associated with marginally with increased risk of death due to heart disease. The numbers involved in this portion of the study are very low and the actual increased risk is also very small (0.12%) I don’t believe there is anything to worry about.


Because this subject is so important and it has insinuated itself into brains of so many scientists, physicians, news media reporters and the public in general, I believe a detailed account of the problems with these studies should be provided. Hence, the following.

In their review Mozaffarian et al (1) present a summary table which shows the relative risk (RR) and the 95% confidence intervals (CI) found in four prospective cohort studies. As usual I will present the data from each of the studies in the review and evaluate the authors risk estimates by making graphs using their data.

Study 1. Ascherio et al (2)

One of these studies which is often quoted as demonstrating that trans fat intake is linked to elevated risk of heart disease was published by Ascherio et al.(2). This is an important paper in many ways because it also presents data that shows no increased risk in the incidence of heart disease due to intake of saturated fat or cholesterol. Hasn’t been too long ago that every one believed they were dangerous dietary bad actors. Many people still do and this is partly due to the failure of the governmental agencies and news media to inform the general public of this change in belief.

In Ascherio et al (2) people were categorized according to the intake of the various kinds of fat (grams/day) and the incidences of heart attack (myocardial infarct, MI) were recorded (Figure 1).

Figure 1. The relative risk (RR) of myocardial infarct (MI) as a function of the intake of saturated fat or cholesterol. The data points show the RR plus and minus the 95% confidence intervals. The intake categories are shown on the X axis and reflect the amount of each fat in grams/day. The lowest amount is 1 and the highest is 5. The dashed line represents the no effect level of 1.0.

It is clear that intake of saturated fat or cholesterol is not related to any increase risk of MI. This conclusion has been confirmed in several more studies some of which are discussed in the following sections.

In this same study the authors examined for any relationship that might exist between trans fat and the risk of heart disease. Their data are shown in Figure 2. There is no significant increase in myocardial infarction (MI) in the 2 - 4 categories which represent from 2.2 to 3.3 grams/day of trans fat. The intake in category 1 was 1.5 gm/day. The only statistically significant group was the people who consumed 4.3 gm/day (category 5). So my conclusion from these data would be that a very weak suggestion of an increase risk of MI was found in group 5. By “weak suggestion” I mean barely statically significant and may not be real.

When the authors adjusted their data for fiber intake there was no hint of and increase in risk due to trans fat intake. It has been suggested that increased dietary fiber intake significantly reduces heart disease (3). The correction for fiber intake is based on the data that show people who consume a fatty diet also consume less fiber. Since fiber is presumed to be protective against MI the incidence increases when dietary fiber intake is low (3). I am not sure we can believe this any more than anything else in these papers. One conclusion you could draw from these data is trans fat is not the problem and it may be the lack of fiber.

Figure 2 The relative risk (RR) of myocardial infarct (MI) without (A) and with (B) correction for dietary fiber intake. The RR plus and minus the 95% confidence intervals are shown as a function of amount of dietary trans fat The intake categories are shown on the X axis and reflect the amount of each trans fat in grams/day. The lowest amount is 1 and the highest is 5.

Adding to my lack of enthusiasm concerning any elevated risk of MI due to dietary intake of trans fats is the following incidence data shown in Figure 3. As you can see the incidence of MI in the three fat groups appear to be almost identical. This makes it very difficult to accept that any significance can be granted to trans fat group and not to the other groups. In most of these kinds of papers the incidence data are not shown. I believe you can guess the reason.

From these data in Figure 3 the actual risks can be calculated. I will do this for trans fat only, the others are similar. The authors calculate a RR of 1.40 with a 95% CI (1.1 -1.79) and would say there is a 40% increase in the risk of MI due to trans fat intake. Note that the lower value for CI is 0.1 away from non-significant. It gets worse, when you calculate the actual increase which is 0.12%. So even if the actual risk were significant the odds of adverse effects from consuming trans fats are small indeed.

Figure 3. Incidence of myocardial infarct as function of dietary fat. Percent incidence calculated from the raw data in Ascherio et al (1). Fat intake categories are the same as in Figure 2 above.


Ascherio et al (1) also examined the risks of fatal heart disease and dietary fat. The number of people who died in these studies was very small which makes any conclusion concerning these data very suspect. The RR’s for increased death rate in the saturated fat group were not significant except in the highest intake category (RR = 2.21 95% CI, 1.38 - 3.54, see Figure 4 A). The actual increased risks is 0.08%. The amount of cholesterol in the diet did not have any significant effect on the risk of death due to CHD (Fig 4 B).

Figure 4. The relative risk of death due to CHD in relation to saturated fat (A) and cholesterol (B)

Trans fat appeared to elevate the risks of death (Fig 5 A); however, when these data were corrected for fiber intake the risks became non-significant (Fig. 5 B). The actual difference in risks between the lowest intake category (0.07%) and the highest (0.12%) was 0.05%. These very small numbers add to the doubt that an statistical significance can be ascribed to these data.

As indicated previously, if any significant increase in the risk of CHD in people who consume a lot of trans fat it is not due to the fat, but the lack of fiber. So don’t blame the fat, blame the lack of fiber

Figure 5 The relative risk of death due to dietary intake of trans fats. The multivariate adjusted relative risks are shown in A and these risks corrected for fiber intake are shown in B.

Study 2 Nurse’s Health Study (NHS) by Oh et al (4).

In this paper women were studied for 20 years and the incidence of heart disease and dietary fat intake were compared. The NHS data are important because they show no increase in risk for the following forms of fat:

· Total fat,

· Saturated fat,

· Mono-unsaturated fat

· Poly-unsaturated fat.

These studies are exemplified by Figure 6 A which shows that dietary saturated fat intake does not increase the risk of coronary heart disease (CHD). Dietary intake of poly unsaturated fat appears to result in a reduced risk of CHD (Figure 6 B). Once again the data are weak and with only one RR (category 5) showing any significant decrease. It is difficult to say with any confidence that the risks of CHD are reduced by eating poly unsaturated fats.

Figure 6 Relative risk of coronary heart disease and dietary intake of saturated and poly unsaturated fat. The energy intake categories represent the percent of energy derived from the specific fat in question. Category 1 being the lowest and 5 the highest.

The results for trans fat study are weak in the opposite direction (Figure 7). That is, they show and upward trend and thus hint at an increased risk of CHD due to dietary trans fat but once again the data in support of this are weak. In category 2 the RR is clearly not significantly different from the no effect line of 1.0. However the level for category 3 is elevated above the no effect line. But, then the RR for category 4 decreases and is not elevated significantly above 1.0. In the final category (5) the RR of 1.33 is elevated but the 95% CI (1.07 -1.66) just barely misses crossing 1.0. No data are provided on the incidence of CHD in each category so I was not able to draw a graph of these data as I did in Figure 3 above. The RR of 1.33 is the one published in the review by Mozaffarian et al (1), and no mention is made of the tenuous nature of its information or that decrease intake of fiber was taken into account.

Figure 7. Relative risk of coronary heart disease and dietary intake of trans fat. The energy intake categories are explained in caption of figure 4.

Study 3. Zutphen Elderly Study by Oomen et al (5). Written for the scientist.

In this study older men (age 64-84) were studied for 10 years and their trans fat intake was correlated with risk of CHD. The authors concluded that there was an increase in CHD with a 2% increase in dietary trans fat. This was based on a RR of 1.28 and (95% CI of 1.01 – 1.61). This looks like another barely significant RR and I advise waiting until the data form next years’ study is available before you make up your mind. No data on incidence or relative risk as a function of fat intake were given in this paper; therefore , it is difficult to judge it’s value.

Study 4. The Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study by Pietinen et al (6).

This is an important study because the authors conclude that risks of CHD are not associated with dietary intake of the following nutrients:

· Saturated fat

· Cholesterol

· Cis-monounsaturated fats

· Total triglycerides,

· Saturated fatty acids

· C12 – C16 Saturated fatty acids.

These authors also report that linoleic and linlenic acids are not associated with increase or decrease risk of CHD. These findings concerning linoleic and linolenic acid are in contradiction to some of the more recent studies which have claimed these two fatty acids decrease the risks of CHD (4).

In their analysis of trans fat they did not show any significant increase in the risk of non-fatal CHD; however they claim that fatal CHD is increased by trans fat intake. Figure 8 shows that the only RR of significance is for the highest intake category ( RR 1.39 95% CI 1.09-1.76). In light of the up and down nature of the preceding values, none of which come close to being statistically significant, it is likely that 1.39 is also not significant. If a correction for fiber intake had been used it probably would not be significant. The actual increase risk in this case is only 0.16% compared to the 39% relative risk.

Figure 8. Relative risk of fatal CHD and dietary intake of trans fats. Data taken from Pietinen et al (6).

Retrospective case-control studies

The remaining studies included in the review by Mozaffarian et al (1) were retrospective case-control studies which have smaller numbers of individuals involved and are less likely to be valid.

In the first study the content of fatty acids in adipose tissue was examined in 671 men in 8 European countries and Israel with acute myocardial infarction (7). The odds ratio was 0.97 (95% CI 0.56-1.67) and obviously not statistically significant. So, no evidence for an increase in the risks of CHD due to fatty acids was found.

The second study also examined the content of fatty acids in adipose tissue but this time in Costa Rica (8). They examined their data by adjusting the values according to the following scheme. First they adjusted the data for income, history of diabetes , history of hypertension, physical activity , smoking, years living in the house and alcohol intake (Figure 9 A). As you can see, this adjustment made the odds ratios increase but not significantly (Fig 9 B). So they tried further adjustments for adipose tissue, linolenic acid and intake of vitamin E, saturated fat and total energy. These adjustments finally gave the authors a statistically significant increase in the odds ratio in group 5 of OR 2.94 (95% CI 1.36-6.37); Figure 9 C. This is the value in table 2 of the review by Mozaffarian et al (1). No mention of the non-significant odds ratios in the first two adjustments. The possibilities for errors in a study containing so many adjustments, some valid and some may be not, make the final odds ratio very suspect and not credible.

Figure 9. Odds ratios and risk of myocardial infarction as a function of the amount of trans fatty acid in adipose tissue. All data taken form table 3 in Baylin et al (8).

The last study listed in the review is an Australian study which involved 209 cases of myocardial infarction (9). The relative risk of MI in the highest category of dietary intake was 2.25 (95% CI 1.16-4.32), and this value was published in Figure 4 in the review by Mozaffarian et al (1). I have plotted the RRs for each intake category in Figure 10 A below and it is obvious the only the last RR is statistically significant. However, this increase in risk was due to decline in the number of people in the control group (see Figure 10 B) which was accompanied by a similar increase in the number of cases of MI. The true RR would have been considerablely lower if the number in the control group had not taken a sudden an unexplained drop.

Figure 10. Dietary intake of trans fat and first myocardial infarct (MI). These data taken from table in Clifton et al (9).


Evidence that trans fatty acids in the diet elevate the risk of CHD is very weak and if the lack of fiber in the diet is taken into consideration there is no significant increased risk of CHD due to dietary trans fat.

These studies demonstrate that the following fats do not increase the risk of CHD:

· Total fat,

· Saturated fat,

· Cholesterol

· Mono-unsaturated fat

· Poly-unsaturated fat

· Cis-monounsaturated fats

· Total triglycerides,

· C12 – C16 Saturated fatty acids.


Some important studies which were not included in the Mozaffarian review (1) will be discussed in this section.

For historical and prophetic reasons the study by Micheal DeBakey’s group published in 1964 should be mentioned (10). They analyzed serum cholesterol values in 1700 patients and found no correlation between cholesterol and atherosclerotic disease. Apparently no one listened and cholesterol was declared the enemy. The battle went on for years, but as you can see from the review of the preceding paper and by ref 11 below, cholesterol has be exonerated by many people.

A large prospective study involving 80,082 women 34 to 59 years of age seems important not only because of its size but for the many different fats studied (11). They found no increase risk of CHD as a result of the following dietary fats:

· Total fat

· Animal fat

· Vegetable fat

· Saturated fat

· Mono-unsaturated fat

· Poly-unsaturated fat

· Cholesterol

The only item on their study menu which showed even the slightest increased risk was trans fat and then only in the highest intake category (Figure 11). It is hard to believe that the RR for this group 1.27 (95% CI 1.03-1.56) is of any significance since the amount of trans fat intake in category 5 differs from category 4 by only 0.05%. This is very weak data point and lacks credibility. No numbers of individuals were given in this paper so the actual risks could not be calculated.

Figure 11. Relative risk of CHD as function of trans fat intake. Data from table 3 in Hu et al (11

In a follow-up study these authors say that diet high in fat and low in carbohydrates is not associated with increased risk of heart disease (12). They seemed surprised by their findings. Maybe they should read their own paper.


Although dietary cholesterol was declared the enemy years ago, the signs that this was not true were provided by none other than Micheal Debakey back in 1964 (10). He has since been proven to be correct. The other highly touted villains in our diet like total saturated fat and animal fat have also bitten the dust. The latest epidemiologist’s horse by the name of trans fats appears to be stumbling and may fall in the future. I believe it has already fallen judging by the marginal data which is said to support its dangers.


1. Mozaffarian et al 2006 Trans fatty acids and cardiovascular disease. NEJM 354:1601-1613.

2. Ascherio A, Rimm EB, Giovannucci EL, et al. Dietary fat and risk of coronary heart disease in men: cohort follow up study in the United States. BMJ 1996;313:84–90.

3. Rimm EB, Ascherio A, Giovannucci E, Spiegelman D, Stampfer MJ, Willett WC 1996 Vegetable, fruit and cereal fiber intake and risk of coronary heart disease among men. JAMA 275:447-51.

4. Oh K, Hu fB, mason JE, Stampfer MJ Willett WC 2005 Dietary fat intake and risk of coronary heart disease in women: 20 years of follow-up of the Nurses’ Health Study. Am J Epidemiol 161:672-679.

5. Oomen CM, Ocke MC, Feskens EJ, et al. Association between trans fatty acid intake and 10-year risk of coronary heart disease in the Zutphen Elderly Study: a prospective population-based study. Lancet 2001;357:746–51.

6. Pietinen P, Ascherio A, Korhonen P, et al. Intake of fatty acids and risk of coronary heart disease in a cohort of Finnish men: The Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study. Am J Epidemiol 1997;145:876–87.

7. Aro et al 1995 Adipose tissue isomeric trans fatty acids and risk of myocardial infarction in nine countries: the EURAMIC study. Lancet 345:273-278.

8. Baylin A et al 2003 High 18:2 trans-fatty acids in adipose tissue are associated with increased risk of nonfatal acute myocardial infarction in Costa Rican Adults, J Nutr 133:1186-1191.

9. Clifton PM, Keogh JB , Noakes M 2004 Trans fatty acids in adipose tissue and the food supply are associated with myocardidal infarction. J Nutr. 134:874-879.

10. Garrett HE, Horning EC, Creech BG, Debakey M 1964 Serum cholesterol values in patients treated surgically for atherosclerosis. JAMA 189:655-659.

11. Hu FB et al 1997 Dietary fat intakes and the risk of coronary heart disease in women. N Engl J Med 337:1491-1499

12. Halton TL et al 2006 Low-carbohydrate-diet score and the risk of coronary heart disease in women. N Engl J Med 355:1991-2002.

Wednesday, August 11, 2010


Even epidemiologists agree that evidence on meat intake and breast cancer is inconsistent and marginal at best. This is an understatement since if you look carefully at their data there is no convincing evidence that any significant relationship exists. But, as usual they are going to try again and in Ferrucci et al.(2009) British J. Cancer 101, 178 they state that they have shown an elevated risk of breast cancer associated with eating red meat.

But, as usual, I have actually examined their data and it just isn’t so. The following figure shows the hazard ratio (similar to a relative risk) and confidence intervals for five groups of women (age 55-74) based on the amount of red meat they consumed.

Group 1 consumed the smallest amount of meat and 5 the most. So you would expect to see an increase in risk as the amount of red meat consumed goes up,- if eating red meat is related to risk. Which as you can see it is not. The response line is flat and the CIs include the no effect level of 1 with the exception of group 2. Since the women in group 2 are consuming much less meat than groups 3-5 this value is a statistical fluke.

This is one of those papers which contains the actual number of cases of breast cancerper number of person years in each food intake group. Thus, an actual percent can be calculated and these are presented in the following table.

So the actual percent difference between group 1 and group 5 is 0.05% or 5/10,000 which is a very small number and would not be considered to be of any statistical or biological significance.

Well if red meat was not going to show an increase the risk of breast cancer maybe other categories will. So they examined:

1. Steak: No increased risk

2. Hamburger: No increased risk

3. Sausage: No increased risk

4. Bacon: No increased risk

5. Pork chops: No increased risk

6. Processed meat: No increased risk


Try as they might there is no evidence that red meat and other kinds of meat increase the risk of breast cancer.

Sunday, August 8, 2010



Some nutritionist and epidemiologists believe that eating red meat and processed meats may increase the risk of cancer. They are not sure because many of the studies of this subject have been contradictory. However, the belief “that eating anything that tastes that good has to be bad” is always bouncing around in their heads. So they keep looking.

This topic is important because the news media love to tell their audience what they should and should not eat. Especially when the scientists say it could cause cancer. Important note: Often the word could gets left out and the headline reads, “EATING STEAK CAUSES BREAST CANCER”.

Cho and co-workers in 2006 set out to see if the occurrence of breast cancer in pre-menopausal women ages 26 to 46 was increased by eating red meat. This was done even though this same group had concluded from their previous analysis of 20 different studies that eating red meat was not associated with increased risk of breast cancer in either pre-menopausal or post-menopausal women (Missmer et al 2002).

But, they might have overlooked something. So they examined the data from 90,659 women over a period of 12 year and documented 1021 cases of invasive breast cancer (Cho et al 2006). Once again they found no association between red meat intake and the relative risk of breast cancer when all cancer were grouped together in agreement with their earlier analysis (Missmer et al 2002; Fig 1-A). Not giving up that easily they decided to divide the women with breast cancer into two groups: Those whose cancers did not contain estrogen and progesterone receptors (Fig 1-B) and those whose cancers did contain these hormone receptors (Fig 1-C). No association between intake of red meat and breast cancer in the women with receptor negative cancers was observed.

The authors then examined the possibility of any association in receptor positive group. They claim their data show the possibility of an increased risk of breast cancer in the women with the greatest intake of red meat (category 5 in Figure 1-C). However the lack of any upward trend in all of the groups with lower intake (2,3 & 4) makes it likely that the value for category 5 is a statistical fluke and is not significant. Certainly the over all evidence for any increased risk is marginal and as Shapiro (1997) has pointed out, when relative risks (RR) are 2 or lower they do not have the resolving power to distinguish between confounding factors and causation. In other words the RR value of 1.97 with a 95% confidence interval of 1.35 to 2.88 is of no real significance and certainly does not say anything about effects of eating red meat.

It seems obvious to me that when the RRs for groups 2 – 4 show no upward trend and the value for group 4 is lower than group 3 and sudden increase as in group 5 is likely to be due to chance.

Figure 1 The relative risks of breast cancer as a function of red meat intake. These data are taken from Table 2 in Cho et al 2006. Category 1 is the lowest intake and 5 is the highest. Error bars represent 95% confidence intervals and dashed line is the no effect level.

Intake categories are the following:

Servings of red meat in each category

1. 3/wk or less

2. > 3/wk to 5/week or less

3. > 5/week to 1/day or less

4. > 1/day to 1.5/day or less

5. > 1.5/day

You might be wondering why anyone would even think that red meat causes breast cancer other than the belief cited above that “anything that good, must be bad”. One is the possibility that red meat might contain sufficient estrogenic hormones to stimulate breast cancer growth. Most scientist believe the exceedingly low amounts of estrogen in red meat would not make any significant contribution to the amount of estrogen present in body of a pre-menopausal women. The ovaries of these women produce amounts of estrogen which far exceed any small amount of some estrogenic substance found in the diet.

Another potential culprit in the epidemiologist’s arsenal are heterocyclic amines (HCA). These are formed when meat is cooked and over cooked and they have been shown to be carcinogenic in some animal models. However when put to the test in human studies they fall short. For example, one of the studies quoted in their paper which reportedly shows the HCAs in red meat are associated with breast cancer was done by Shina et al 2000. The results of this study do not show any association between HCAs and breast cancer for two of the three amines studied (Figure 2A and 2B) and only a marginal, and I believe insignificant, association between 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP) and cancer (Figure 2C).

Figure 2. Relative risk of breast cancer as a function of heterocyclic amines (HCA) in the diet. The intake categories represent the estimated amount of HCA in the diet. Category 1 is the lowest and 5 is the highest. Error bars represent 95% confidence intervals and dashed line is the no effect level.

Another possible dietary substance which might be blamed is iron. Iron is a very important constituent of hemoglobin and myoglobin and plays a role in other necessary physiological functions. However, iron has been shown in animal studies to increase mammary cancers when the animals are fed large amounts of iron in the diet and when an iron compound is injected under the skin in rats (Liehr & Jones 2001). Subcutaneous injections and dietary levels of iron which are 10 or more times the normal levels are non-physiological and would be very likely to ever occur in humans. Certainly it is difficult to imagine that 1.5 serving/day of red meat could contain a sufficient quantity of iron to make any difference in the amount of iron present in a woman’s body.


I believe the evidence does not support the idea that eating red meat is associated with an increased risk of breast cancer.


Cho E et al 2006 Red meat intake and risk of breast cancer among premenopausal women. Arch Intern Med 166 2253-2259.

Liehr JG, Jones JS 2001 Role of iron in estrogen-induced cancer. Curr Med Chem 7:839-49.

Shapiro S 1997 Do trans fatty acids increase the risk of coronary artery disease? A critique of the epidemiologic evidence Am J Clin Nutr 66(suppl):1011S-7S

Sinha R et al 2000 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine, a carcinogen in high-temperature-cooked meat, and breast cancer risk. J Natl Cancer Inst. 2000 92(16):1352-4.


Since the kinds of data and graphs in my blogs will be unfamiliar to many of you, I am going to try to explain in this section.

Relative Risk (RR) and Confidence Interval (CI).

Relative risks and confidence intervals are usually expressed numerically or in graphic form. I have made a graph which displays four different RRs and their CIs and will try to explain how to interpret them.

Group 1 has a RR of 1.5 and the CI is 1.1 to 2.5 which are generally shown in text form as RR 1.5 ( CI 1.1-2.5). This RR would be considered marginally significant since the lower range of the CI is just above the line for RR of 1 which is called the no effect level or line.

Remember if the range of the CI includes the no effect line of 1 the data are not statistically significant.

Group 2 also has a RR 1.5 (CI 0.8-2.5) but the lower range of its CI is includes the no effect value of 1.. Therefore it would not be considered statistically significant.

Group 3 has a RR 0.5 (CI 0.2-0.9) which is an example of a RR which is showing
a decreased risk. Since the upper range of the CI does not include the no effect level of 1 this RR would be judged to be statistically significant.

Group 4 has a RR 0.5 (CI 0.2-1.1) which is another example of an RR showing a decreased risk. However, in this case the upper range of the CI includes the no effect level of 1 and would not be considered statistically significant.


When two groups are judged to be statistically significant it just means that the two groups are probably not the same. Something is different,- but what?

Such differences could be due to chance as in studies with large confidence intervals which almost include the no effect level.

These types of studies attempt to show associations or correlations between some event and risk of some disorder or problem. Showing that the data are significant does not prove a cause and effect only the possibility of one.

Tuesday, August 3, 2010


If you believe what governmental and nutritional agents are telling you then the answer is yes. But is it really true.

Sometimes these people don’t know what they are talking about. I have looked into the actual evidence that salt intake is bad for you and found that the question is not settled and the answer is probably, No. I also found that the whole subject has been overblown and misrepresented.

There are many clinical and epidemiological studies on the topic of the relationship of salt intake and increased heart and vascular disease (CVD), stroke and death rate and I have reviewed many of them. These studies fall into three categories:

1. Yes, salt intake may be associated with increase risks of cardiovascular disease (CVD), stroke and mortality (References 1-5).

2. No, salt intake does not increase risks of CVD, stroke and mortality (6,7).

3. Surprise, higher salt intake decreased the risks of CVD (1,8-10).

4. Another Surprise, lower salt intake increased risks of CVD and death (9,10).


How could any government agency have the audacity to state that salt intake is dangerous for your health when the scientific literature is full of papers which display such divergent patterns. Obviously something is wrong. A large part of “Something is Wrong” is people in government agencies and nutritional advisors don’t read the scientific papers which are published on this topic. The scientists who write the papers are guided by a lack of objectivity which is present because of the “Band Wagon Effect”. If they get on the wagon they must remain because their funding, reputation and status depend on it.


If you have had all you can take stop reading; however, if you want a more detailed and somewhat more technical explanation then read on.

Some of this bad information comes from scientists who do not take an honest and careful look at their own data. Their presumption that higher intake of salt will be associated with increased CVD, stroke and mortality over shadows their objective analysis of their own data. As an example of such a study I will use the following paper which incorrectly concluded that high salt intake increased risk of stroke and CVD (11).

In this paper by Strazzullo et al.(11) the results obtained from 19 cohort samples from13 studies have been combined and analyzed by a method called meta-analysis. This method brings together the good, the bad and the ugly and lumps them altogether with the hope that the result will fit the bias of the investigators. In this particular meta-analysis the risk of stroke and salt intake were reported for 14 studies, 10 of which showed no significant effect and 4 showed marginal significance, that is, just barely significant. The results are identical for effect of salt intake on cardiovascular disease: total, 14 studies, 10 showed no significant effect and 4 which showed marginal effects. Most scientists would not believe the conclusions of any study in which 71% of the observations showed no effect and 29% showed a marginal effect.

Yet, Strazzullo et al. conclude that high salt intake is associated with a statistically significant increased risk of stroke and cardiovascular disease. They based their conclusions on relative risks plus or minus confidence intervals (CI). In this kind of analysis if the CI does not include 1.0 then the data are considered to be statistically significant. As the number of subjects get higher the amount of error gets lower. Thus, the confidence interval (CI) gets smaller and is less likely to include the control group number of one.

As an example, a single study with a small number of subjects might have a relative risk (RR) of 1.2 with a CI of 0.6-2.4. Because the CI interval includes 1.0 this means the RR of 1.2 cannot be considered statistically significant. Now if you group together more studies as in a meta-analysis the number of subjects gets much larger and reduces the variability which reduces the interval of the CI. As a result one could obtain a RR of 1.2 with a CI of 1.01-2.0 and since this CI does not include 1.0 the RR is claimed to be statistically significant.

This is exactly what happen in the Strazzullo et al. combined studies which indicated a risk for stroke of RR 1.23 ( CI, 1.06-1.43) and for CVD of 1.17 (CI, 1.02-1.32). The RR of CVD became statistically significant when one of the studies (Alderman 1995) which did not agree with their bias was omitted.  Note that the lowest numbers for CI 1.06 for stroke and 1.02 for CVD are so close to 1.0 you have to hold your breath to claim these RRs are of any real significance.

It should also be noted that demonstrating statistical significance does not necessarily mean that the finding is of any biological significance.

NOTE: In another later blog I will discuss this method in more detail.


1. Tunstall-Pedoe H, Woodward M, Tavendale R, A’Brook R, McCluskey MK. Comparison of the prediction by 27 different factors of coronary heart disease and death in men and women of the Scottish heart health study: cohort study. BMJ. 1997;315:722–9.

2. He J, Ogden LG, Vupputuri S, Bassano LA, Loria C, Whelton PK. Dietary sodium intake and subsequent risk of cardiovascular disease in overweight adults. JAMA. 1999;282:2027–34.

3. Tuomilehto J, Jousilahti P, Rastenyte D, et al. Urinary sodium excretion and cardiovascular mortality in Finland: a prospective study. Lancet. 2001;347:848–51.

4. Nagata C, Takatsuka N, Shimizu N, Shimizu H. Sodium intake and risk of death from stroke in Japanese men and women. Stroke. 2004;15:1543–7.

5. Cook NR, Cutler JA, Obarzanek E, Buring JE, Rexrode KM, Kumanyika SK, Appel LJ, Whelton PK. Long term effects of dietary sodium reduction on cardiovascular disease outcomes: observational follow-up of trials of hypertension prevention (TOHP). BMJ 2007 DOI 10.1136/bmj.39147.604896.55.

6. Kagen A, Popper JS, Rhoads GG, Yano K. Dietary and other risk factors for stroke in Hawaiian Japanese men. Stroke. 1985;16:390–6.

7. Cohen JD, Grandis G, Cutler JA, Neaton JD, Juller LH, Stamler J. Dietary sodium intake and mortality: MRFIT Follow-up Study Results (abstract). Circulation. 1999;100(suppl 1):1–524.

8. Alderman MH, Madhavan S, Cohen H, Sealey JE, Laragh JH. Low urinary sodium is associated with greater risk of myocardial infarction among treated hypertensive men. Hypertension. 1995;25:1144–52.

9. Alderman MH, Cohen H, Madhavan S. Dietary sodium intake and
mortality: the National Health and Nutrition Survey (NHANES I)>. Lancet. 1998;351:781–5.

10. Cohen HW, Hailpern SM, Fang J, Alderman MH. Sodium intake and mortality in the NHANES II Follow-up Study. Am J Med. 2006;119:274e7–5e14.

11. Strazzullo P. et al. Salt intake, stroke and cardiovascular disease: meta-analysis of prospective studies. BMJ 2009:339;b4567.

Monday, August 2, 2010


Almost every day the TV is blaring warnings like:


This scares a lot of people because they don’t understand what a 30%
increase in risk really means. If they did understand they wouldn’t give it a second thought. The actual risk in this case is 0.07% which is insignificant but the reader has no way of knowing that.

How can this be?

Very simple, for example a hypothetical study finds that big toe aches occur in 0.04%of people who watch TV. While only 0.02% suffer from toe ache who do not watch TV. So the headline would read “Watching TV increases the risk of big toe ache by 100%”.

A 100% increase sounds terrible until you find out that the number of people in the control group with toe aches was 2/10,000 and the numer in the TV group was 4/10,000. Then it is obvious that the actual increase is 0.02% and not 100%.

100% in this example is called a relative risk which is obtained by dividing the percent increase in the TV group, 0.02, by the percent in the control group, 0.02, which equals 100% ( 0.02/0.02 = 1 x 100 = 100%). Almost all medical studies of this type use this way of expressing percent and usually do not disclose the actual or absolute percent differences.

Knowing the difference between relative risk and the absolute risk is the key to understanding what the truth is behind the news release and relieving the anxiety induced by reading the scary headlines.