FACT CHECK: My first impression of this study is that while they recognize certain factors and results as anecdotal, I find ALL results and assumptions anecdotal because of the nature and uncontrollable variables of the study.
Scientific factors and explanations aside, this study is flawed. This study (by design) does not meet the standards of scientific testing. It is not double blind. The sampling is too small and uncontrolled. There is no represented control over the test subjects and the results are based on blood testing and surveying the participants.. “Since the scoring system in the present study only assessed relative adherence to each of the four ‘Blood-Type’ diets, we could not determine the absolute number of people who strictly followed any of the diets”.True compliance by test subjects is not known.
It is readily and repeatedly stated with different language that residual confounding is: “the observed associations between ‘Blood-Type’ diet scores and cardiometabolic disease risk factors could be due to residual confounding. However, residual confounding is not likely to explain why there would be no differential association among ABO genotypes.” I disagree. For your convenience to understand word phrases, I present a high levelsummary of residual confounding:
Residual confounding is the distortion that remains after controlling for confounding in the design and/or analysis of a study. There are three causes of residual confounding:
There were additional confounding factors that were not considered, or there was no attempt to adjust for them, because data on these factors was not collected.
Control of confounding was not tight enough. For example, a study of the association between physical activity and age might control for confounding by age by a) restricting the study population to subject between the ages of 30-80 or b) matching subjects by age within 20 year categories. In either event there might be persistent differences in age among the groups being compared. Residual differences in confounding might also occur in a randomized clinical trial if the sample size was small. In a stratified analysis or in a regression analysis there could be residual confounding because data on confounding variable was not precise enough, e.g., age was simply classified as “young” or “old”.
There were many errors in the classification of subjects with respect to confounding variables.” (*Confounding and Effect Measure Modification, http://sphweb.bumc.bu.edu/… Boston University of Public Health). The sampling and length of the study is insignificant, There is not enough data (from this study) to make the declaration of “no differential association among ABO genotypes”. To state of (the blood type diet): “its recommendations do not specify any actual amount of consumption.” is materially incorrect and the statement is deceptive.
Dadamo and his book do not make a claim without scientific facts and complete references. This study does not reflect enough of the lectin factor… and a complete dismissal of Dadamo’s (among other) research with regard to specific lectin effect on aglutenation ofeach of the ABO blood types. It is stated: “In summary, the present study is the first to test the validity of the ‘Blood-Type’ diet and we showed that adherence to certain diets is associated with some favorable cardiometabolic disease risk profiles.
This may explain anecdotal evidence supporting these diets, which are generally prudent diets that reflect healthy eating habits. However, the findings showed that the observed associations were independent of ABO blood group and, therefore, the findings do not support the ‘Blood-Type’ diet hypothesis.” this statement corresponds to the preferred result of nutrigenomics who appear to focus less on the blood type and more on genetic factors. They say there is no corresponding conflict and the fact a grant from nutrigenomics helped pay for this “OPINION PAPER”.
Peer review is a mis-used phrase and implies real science where it is generally evaluation of meta-data and not real science.
MY INDIVIDUAL CASE STUDY: I started the blood type diet, not to lose weight… my weight was already dropping from me via an eating disorder called… “I don’t feel like eating get that food away from me.” Or more commonly referred to as PTSD. I had to go about the task of finding a “DIETary” lifestyle that allowed me to eat without wanting to vomit or the smell of food that would would make me nauseated. I actually selected the blood-type diet because of the foods, which made food preparation easier with more raw foods and vegetables.
The first meal of the day is still difficult for me… and if I don’t have reminders, I will usually forget to eat all day long and around supper time say… humm… I haven’t eaten anything all day. As far as my health. At the start, I was in the middle of a cardiac intervention… pulmonary intervention… and anemia that followed me my entire life… no matter what treatment was tried. In 2009/2010, my carotid and femoral arteries had significant plaque. I had a leaky heart valve. I had an aFib issue and was told I would be on heart medication the rest of my life. I had peptic ulcers, edema of the transverse colon… I can’t remember what I have forgotten to list I was at the door of death and passed through it when as a man, I waited beyond the point of no return before I went to the ER… where I coded on Oct 17, 2009 when two of four heart chambers were crushed by fluid. I was conscious and watched the flatline that lasted about 15 seconds. This all came to a head after eating SUSHI… where I got a food borne bacteria… not e.coli, or any other type of food poisoning… In fact, after a two week hospitalization it was another three weeks before they were able to determine what had made me accumulate fluids. Three liters in the right lung (pleural effusion) and 550cc’s in my pericardia (pericardial effusion).
Draining the lung was simple enough and I was amused when the fluid was coming out of the tube inserted between a few ribs in my back… saying… “wow, all that is coming out of me?”… The pericardiocentesis (spelling) was a bit more complicated. I had no blood pressure when laying flat so they could not sedate me for the procedure to insert the chest tube to drain my pericardia… so… I had to man up and take the needle and tube going snap crackle pop through my chest wall and into the pericardia and wrapped around the heart with NO SEDATION… I suppose the training I received as a child getting dental care done all the way to exposed nerves with no Novocain (as a form of punishment) was helpful. It was NOT comfortable and was made tolerable by watching the ultra-sound guided tour of the needle and tube in my chest. Remarkably… the initial insertion of the needle was surprisingly painless, but for the look on the cardiologist’s face as he was trying to shove the needle into my chest and asking the ultra sound tech… “Is that the right ventricle?.
I was the walking dead getting five different antibiotics (IV) and was walking around with a fifty foot oxygen hose and a pole with seven infusers on it. They didn’t know what they were treating so they treated everything. At this time I normally had high blood pressure (but not during the intervention). Total cholesterol almost 300. Triglycerides over 400. Low RBC (<4.1), low WBC(<3.8), low hemoglobin(<12.9), low platelets (<135), high MCV (>106) causing macrocytosis (spelling). A wild range of glucose (fasting). Along came the choice of the blood-type diet.
I have a good relationship with my primary care physician and I went to him to tell him what I was going to do… He was a bit indifferent at first… but after a full year he finally said… “I’m not really sure exactly what you are doing, but it is working”… so keep doing it and don’t worry about being too skinny, because you are not… you do have low % of bdy fat but normal BMI”… Thank you Dr Dino Gonzalez.
All of my blood markers are NOW within normal range. A lifetime of anemia has been for all practical purposes completely resolved. There is no cure, but I am as close as it comes. Total cholesterol is now hovering between 140-150, Triglycerides 93. The only blood marker out of range at last blood testing (12/18/2k13) is creatinine (0.7). I no longer take blood pressure medication. I no longer take a statin and before that tricor. I no longer need iron supplementation, which never really helped the anemia but kept me out of crisis. I have not had to have a blood transfusion in three years. My blood pressure is 110/70 (+/-). My resting heart rate is 63 with no aFib or heart medication.
At the start of this in 2009 I weighed 205. After the hospitalization I was down to 170 and went back up to 185 after discharge when resuming (ab)normal carnivorous diet. Those blood markers have to be combined with the fact I now hover between 140-145lbs and have been there for two years now. % of body fat about 11%, BMI 22, bone density 66. I am released from cardiac care. The plaque that WAS in my carotid and femoral (among other places I’m sure) is COMPLETELY GONE. I have no aFib. I don’t have a six pack stomach… I have an eight pack stomach. My peptic ulcers are gone. The edema of my transverse colon (IBS) is gone. There are other resolved minor issues.
I am the picture of health… other than a pulmonary embolism in September which there as of yet is no explanation for. I do not fit the profile of sedentary lifestyle… so it may end up being a little chunk of the big “C” somewhere. Nothing invasive to explore can be done because i’m on rat poison… coumaden/warfarin, which took me from the blood type diet to the warfarin diet.
The latest lab results were after three months of NOT eating the vegetables, nuts, grains, seeds, legumes, seafood and all other foods high in vitamin K that resolved so many of my medical issues… including completely reversing cardiovascular disease but for that pesky right lung. I haven’t been an angel my whole life and the 2009 crisis uncovered, stage 1 emphysema, asthma, severely reduced lung capacity just n the right lung and a lot of scar tissue. I did not start the blood type diet to lose weight but rather gain health. I am the poster boy BUT… according to this “peer-reviewed” piece it doesn’t count because I am blood type A+. ANY QUESTIONS???
ABO Genotype, ‘Blood-Type’ Diet and Cardiometabolic Risk Factors
- Jingzhou Wang, Bibiana García-Bailo, Daiva E. Nielsen, Ahmed El-Sohemy
Published: January 15, 2014
The ‘Blood-Type’ diet advises individuals to eat according to their ABO blood group to improve their health and decrease risk of chronic diseases such as cardiovascular disease. However, the association between blood type-based dietary patterns and health outcomes has not been examined. The objective of this study was to determine the association between ‘blood-type’ diets and biomarkers of cardiometabolic health and whether an individual’s ABO genotype modifies any associations.
Subjects (n = 1,455) were participants of the Toronto Nutrigenomics and Health study. Dietary intake was assessed using a one-month, 196-item food frequency questionnaire and a diet score was calculated to determine relative adherence to each of the four ‘Blood-Type’ diets. ABO blood group was determined by genotyping rs8176719 and rs8176746 in the ABO gene. ANCOVA, with age, sex, ethnicity, and energy intake as covariates, was used to compare cardiometabolic biomarkers across tertiles of each ‘Blood-Type’ diet score.
Adherence to the Type-A diet was associated with lower BMI, waist circumference, blood pressure, serum cholesterol, triglycerides, insulin, HOMA-IR and HOMA-Beta (P<0.05). Adherence to the Type-AB diet was also associated with lower levels of these biomarkers (P<0.05), except for BMI and waist circumference. Adherence to the Type-O diet was associated with lower triglycerides (P<0.0001). Matching the ‘Blood-Type’ diets with the corresponding blood group did not change the effect size of any of these associations. No significant association was found for the Type-B diet.
Adherence to certain ‘Blood-Type’ diets is associated with favorable effects on some cardiometabolic risk factors, but these associations were independent of an individual’s ABO genotype, so the findings do not support the ‘Blood-Type’ diet hypothesis.
Citation: Wang J, García-Bailo B, Nielsen DE, El-Sohemy A (2014) ABO Genotype, ‘Blood-Type’ Diet and Cardiometabolic Risk Factors. PLoS ONE 9(1): e84749. doi:10.1371/journal.pone.0084749
Editor: Nick Ashton, The University of Manchester, United Kingdom
Received: August 15, 2013; Accepted: November 18, 2013; Published: January 15, 2014
Copyright: © 2014 Wang et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This work was supported by grant 305352 from the Advanced Foods and Materials Network (to AE-S). JW is a recipient of an Ontario Graduate Scholarship. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: AE-S holds shares in Nutrigenomix Inc., a genetic testing company for personalized nutrition. This does not alter the authors’ adherence to all the PLOS ONE policies on sharing data and materials.
A link between ABO blood group and diet was proposed by P.J. D’Adamo in his book “Eat Right For Your Type” published in 1996 . The ‘Blood-Type’ diets have gained widespread attention from the public with more than 7 million copies sold in over 60 languages, and making the New York Times bestseller list . D’Adamo postulates that the ABO blood group reveals the dietary habits of our ancestors and adherence to a diet specific to one’s blood group can improve health and decrease risk of chronic diseases such as cardiovascular disease. Based on the ‘Blood-Type’ diet theory, group O is considered the ancestral blood group in humans so their optimal diet should resemble the high animal protein diets typical of the hunter-gatherer era. In contrast, those with group A should thrive on a vegetarian diet as this blood group was believed to have evolved when humans settled down into agrarian societies. Following the same rationale, individuals with blood group B are considered to benefit from consumption of dairy products because this blood group was believed to originate in nomadic tribes. Finally, individuals with an AB blood group are believed to benefit from a diet that is intermediate to those proposed for group A and group B . The ‘Blood-Type’ diet also proposes that lectins, which are sugar-binding proteins found in certain foods , could cause agglutination if they are not compatible with an individual’s ABO blood group.
The ABO blood group is a classification of blood based on the structural variation of a certain carbohydrate antigenic substance on red blood cells. As one of the first recognizable genetic variants in humans, the ABO blood group has been studied extensively for its association with a variety of diseases including cancer , , , , malaria , and cholera . Regarding cardiometabolic diseases, individuals with blood group O were found to have lower levels of von Willebrand factor (VWF)  and had a reduced risk of venous thromboembolism compared to the other blood groups . Furthermore, group B individuals were found to have lower levels of E-selectin  and a lower risk of type 2 diabetes compared to group O . These findings demonstrate the potential importance of the ABO blood group in altering risk of disease, including cardiometabolic disease. However, little is known about whether the ABO blood group modifies an individual’s response to diet. A recent systematic review concluded that no evidence exists to support the proposed health benefits of ‘Blood-Type’ diets . Considering the lack of scientific evidence and the popularity of the ‘Blood-Type’ diet, the objective of this study was to determine the association between ‘Blood-Type’ diets and biomarkers of cardiometabolic health and whether an individual’s ABO genotype modifies any associations.
Materials and Methods
Subjects (n = 1,639) were participants of the Toronto Nutrigenomics and Health (TNH) Study, which is a cross-sectional examination of young adults aged 20 to 29 years. All subjects were recruited between October 2004 and December 2010 and completed a general health and lifestyle questionnaire, which included information on age, sex, ethnocultural group and other subject characteristics. Subjects who were likely under-reporters (less than 800 kcal per day) or over-reporters (more than 3,500 kcal per day for females or 4,500 kilocalories per day for males) of energy intake were excluded from the analyses. Subjects were also excluded if they had missing data for any of the biomarkers of interest or ABO genotype (n = 184). After exclusions, 1,455 subjects (993 women and 462 men) remained. Individuals were categorized into four major ethnocultural groups: White (n = 703), East Asians (n = 491), South Asians (n = 155), and others (n = 106).
Dietary adherence score assessment
Dietary intake was assessed by a one-month, Toronto-modified Willet 196-item semi-quantitative food frequency questionnaire (FFQ) as described previously . Briefly, each subject was given instructions on how to complete the FFQ by using visual aids of portion sizes to improve the measurement of self-reported food intake. Subject responses to the individual foods were converted into daily number of servings for each item. In order to quantify the adherence to each of the four ‘Blood-Type’ diets, four different diet scores were given to each subject regardless of his or her own blood group. Based on the food items listed in the ‘Blood-Type’ diets , subjects received one positive point for consuming one serving of each recommended food item and one negative point for consuming one serving of an item on the list of foods to avoid. Foods that are listed as “Neutral” were not included in the equation and do not contribute to the final score. The lists of recommended foods to eat or avoid for each ABO blood group are shown in the Appendix S1. Subjects were then grouped into tertiles based on their scores for each diet, with the top tertile representing those whose diet most closely resembles the corresponding ‘Blood-Type’ diet.
Cardiometabolic risk factor assessment
Anthropometric measurements including height, weight, blood pressure and waist circumference were determined as previously described . Body mass index (BMI; kg/m2) was calculated and physical activity was measured by questionnaire and expressed as metabolic equivalent (MET)-hours per week, as described previously , . Overnight 12-hour fasting blood samples were collected to measure serum biomarkers of cardiometabolic disease including triglycerides, free fatty acids, C-reactive protein, glucose, insulin, and total-, HDL- and LDL-cholesterol, as described previously . The homeostasis model of insulin resistance (HOMA-IR) was calculated by using the formula: (insulin * glucose)/22.5, and the homeostasis model of beta-cell function (HOMA-Beta) was calculated by using the formula: (20 * insulin)/(glucose – 3.5).
ABO genotype identification
The Sequenom MassArray® multiplex method was used to determine the blood group of study participants by genotyping two single nucleotide polymorphisms (SNPs) (rs8176719Del>G; rs8176746A>C) in the ABO gene. The rs8176719 SNP indicates O-allele-specific 261delG while rs8176746 determines the galactose specificity of the encoded A/B transferases and thus the expression of A and B antigens on erythrocytes .
Statistical analyses were performed using the Statistical Analysis Systems (SAS) Software program (version 9.2; SAS Institute Inc., Cary, North Carolina). The a error was set at 0.05 and reported p-values are 2-sided. Variables that were not normally distributed were either loge or square root transformed prior to analysis, but the mean values and standard errors are displayed without transformation to facilitate interpretation. Subject characteristics were compared across ABO blood groups by using chi-square tests for categorical variables and analysis of covariance (ANCOVA) for continuous variables. ANCOVA was also used to compare means of biomarkers of cardiometabolic disease risk across tertiles of diet scores. Means compared between groups were adjusted for multiple comparisons using the Tukey-Kramer procedure. Age, sex, ethnocultural group and energy intake were used as covariates in the ANCOVA analysis. Physical activity and smoking were also considered, but not included in the final model because they did not significantly (P<0.05) alter the results. The p-values for the associations between ‘Blood-Type’ diet and cardiometabolic biomarker profile remained significant (P<0.001) regardless of whether or not these two variables were included in the model. To determine whether matching the blood group with the corresponding diet was associated with a more favorable cardiometabolic disease risk profile, we stratified the entire population into two groups; one with the matched blood group for the diet, and the other unmatched. We next examined the interaction between diet score and the matching status on levels of each cardiometabolic disease risk factor for each ‘Blood-Type’ diet by using the Tukey-Kramer correction. When a significant interaction effect was observed, we further compared the differences in the outcome between subjects with the matched blood group and the unmatched group in each of the tertiles of diet score.
Subject characteristics based on the ABO blood group are summarized in Table 1. After adjusting for age, sex, and ethnocultural group, subject characteristics were similar across ABO blood groups, except for insulin, HOMA-IR and HOMA-Beta (p<0.05). Although the overall association between blood group and total cholesterol was significant (p = 0.043), no difference was observed among specific ABO blood group.
Table 1. Subject Characteristics by ABO Genotypea.
Each ‘Blood-Type’ diet was first examined in the entire population without considering ABO blood groups. Figure 1A shows the total number of recommended items that were included in the FFQ for each diet. Briefly, the Type-A diet recommends high consumption of grains, fruits, and vegetables. The Type-B diet recommends high intakes of dairy products and moderate intakes of other food groups. The Type-AB diet is similar to the Type-B diet, but has more restrictions on specific food items. For example, only eggs and fish are recommended as sources of meat for group AB individuals (Appendix S1). The Type-O diet promotes high consumption of meats and avoidance of grain products. Figure 1B shows the diet score distribution. All four scores were normally distributed and did not require any transformation.
Figure 1. ‘Blood-Type’ diet (A). Diet score distribution for each ‘Blood-Type’ diet (B).
Characteristics of each ‘Blood-Type’ diet according to tertile of diet score are summarized inTable S1. Consistent with its recommendations, subjects in the highest tertile of the Type-A diet score consumed more fruits and vegetables and less meat (P<0.001). As for the two diets that recommend dairy consumption, high adherences to the Type-B and Type-AB diets were associated with higher intakes of dairy products (P<0.05). The dietary intake of those following the Type-O diet was also consistent with the diet’s recommendations where more meat and less grain products were consumed as individuals adhered more closely to the Type-O diet (P<0.001).
Mean levels of cardiometabolic disease risk factors based on the tertiles of each diet score are shown from Table 2 to Table 5. All associations were adjusted for age, sex, ethnocultural group and energy intake. With increasing adherence to the Type-A diet, subjects, regardless of their ABO blood group, had lower BMI, blood pressure, waist circumference, serum total cholesterol, triglycerides, insulin, HOMA-IR, and HOMA-Beta (P<0.05). Adherence to the Type-AB diet was associated with lower blood pressure, serum total cholesterol, triglycerides, insulin, HOMA-IR, and HOMA-Beta (P<0.05). Adherence to the Type-O diet was associated with lower serum triglycerides (P<0.001). Although the overall association between the Type-B diet adherence and the level of HDL-cholesterol was significant (p = 0.04), no difference was observed between each tertile of the diet score.
Table 2. Cardiometabolic Risk Factors by the Tertiles of Type-A Diet Scorea.
Table 3. Cardiometabolic Risk Factors by the Tertiles of Type-B Diet Scorea.
Table 4. Cardiometabolic Risk Factors by the Tertiles of Type-AB Diet Scoresa.
Table 5. Cardiometabolic Risk Factors by the Tertiles of Type-O Diet Scoresa.
Table 6, 7, 8 and 9 show the associations between diet scores and cardiometabolic disease risk factors according to the ABO blood group. Different ABO blood groups were equally distributed across the tertiles of each diet score. No significant interactions were observed between diet score and blood group for most of the risk factors, except for fasting glucose (P = 0.02), insulin (P = 0.02), and HOMA-IR (p = 0.01) in the Type-A diet (Table 6), and fasting glucose (P = 0.02) in the Type-AB diet (Table 8). When comparing the levels of fasting insulin and HOMA-IR between group A individuals and the other blood groups, a significant difference was observed in the second tertile, but not in the lowest or highest tertile of the Type-A diet score. No difference in fasting glucose was observed between the two groups in any tertile of the Type-A diet score. For fasting glucose in the Type-AB diet, no difference was observed between individuals with blood group AB and those with other blood groups in any tertile.
Table 6. Cardiometabolic Disease Risk Factors by Matching Type-A Diet Scores and ABO Genotypea.
Table 7. Cardiometabolic Risk Factors by Matching Type-B Diet Scores and ABO Genotypea.
Table 8. Cardiometabolic Risk Factors by Matching Type-AB Diet Scores and ABO Genotypea.
Our findings show that adherence to certain ‘Blood-Type’ diets is associated with a favorable profile for certain cardiometabolic risk factors in young adults, but these associations were not related to an individual’s ABO blood group. To our knowledge, this is the first study to examine the association between the ‘Blood-Type’ diets and biomarkers of cardiometabolic health, and the findings do not support the ‘Blood-Type’ diet hypothesis.
The association between the Type-A diet adherence and favorable cardiometabolic risk profile is not surprising considering this diet’s emphasis on high consumption of fruits and vegetables, and low consumption of meat products, which is similar to a dietary pattern that has been recommended by various health agencies because of its association with a lower risk of cardiovascular diseases , , , , . Adherence to the Type-AB diet was also associated with favorable levels of several risk factors, despite its recommendation for certain dairy and meat products. Such benefits may be attributed to the list of certain food items considered healthy, which are recommended. For example, individuals with blood group AB are advised to avoid butter and to consume eggs and fish as their main animal-protein source. This is in contrast to the Type-B diet, which has fewer restrictions on many animal products as shown in the Appendix S1. These differences between the two diets may partially explain why a favorable cardiometabolic profile was associated with adherence to the Type-AB diet, but not for the Type-B diet. The Type-O diet is similar to low-carbohydrate diets , which may explain why adherence to this type of diet was associated with lower serum triglycerides (TG), as previously observed for other low-carbohydrate diets , . The reduction in TG may be caused by decreased TG production in the liver and/or increased cellular uptake of TG in response to low carbohydrate intake . By investigating the ‘Blood-Type’ diets in a population with different ABO genotypes, we found that adhering to the Type-A, Type-AB, or Type-O diets was associated with favorable effects on levels of certain biomarkers of cardiometabolic disease risk.
In order to examine whether individuals would benefit more from following their own ‘Blood-Type’ diet, the levels of cardiometabolic disease risk factors were compared between individuals with the matched blood group and the unmatched blood group while sharing similar diet adherence. However, no significant interaction effects were observed between diet adherence and blood group for most of the risk factors, suggesting that effects of following ‘Blood-Type’ diets is independent of an individual’s blood group. Although there were significant interaction effects for fasting glucose, insulin and HOMA-IR for the Type-A diet, and fasting glucose for the Type-AB diet, those interactions may be due to chance, since we did not apply the most conservative Bonferroni post-hoc test to correct for multiple comparisons. Even if the interaction effects were not due to chance, those findings would not support the claim that matching the ‘Blood-Type’ diet with the corresponding blood group results in more favorable effects. In the case of the Type-A diet, the significant interaction effects were mainly driven by higher levels of insulin and HOMA-IR in the second tertile for those with blood group A. Moving from low adherence to high adherence, group A individuals did not demonstrate more favorable changes in these biomarkers. As for fasting glucose levels with the Type-AB diet, subjects with blood group AB had slightly higher glucose concentrations as they adhered to the diet more closely, while the other blood groups showed no differences. These findings, therefore, demonstrate that matching the diet with the corresponding blood group was not associated with any additional benefits and may even be associated with some adverse effects. For those in the unmatched blood group, we also tested whether each ‘Blood-Type’ diet was associated with any of the outcomes by matching to each of the other blood groups (data not shown); however, no significant interactions were observed. Therefore, the associations observed with the ‘Blood-Type’ diets were unrelated to any individual blood group.
Several previous studies have questioned the validity of the ‘Blood-Type’ diets. Based on phylogenetic analysis of human ABO alleles, blood group A has been suggested to be the ancestral human blood group , , rather than group O as postulated by D’Adamo . As for the claim that certain food items contain lectins incompatible with an individual’s ABO blood group, studies to date suggest no ABO-specific agglutination . The absence of scientific evidence was further supported by a recent systematic review , which found no study that directly investigated the effects of the ‘Blood-Type’ diet.
The present study has some limitations. The use of FFQs for dietary assessment could result in some measurement error and cannot give a precise estimate of the absolute intake of food items. However, a FFQ is considered a valid instrument for providing relative estimates of food intake in large populations . Although we adjusted for age, sex, ethnocultural group and energy intake and tested physical activity and smoking as potential covariates, the observed associations between ‘Blood-Type’ diet scores and cardiometabolic disease risk factors could be due to residual confounding. However, residual confounding is not likely to explain why there would be no differential association among ABO genotypes. The study population consisted of an unequal distribution of different ethnocultural groups, which have been shown to have a different prevalence of ABO blood groups  and might have different dietary patterns . However, the associations between diet adherence and levels of biomarkers were still evident after adjusting for ethnocultural group. Previous studies using diet scores have quantified relative adherence by deriving the score proportionally based on the recommended amount of consumption . However, this approach would not be appropriate for quantifying the adherence to the ‘Blood-Type’ diet because its recommendations do not specify any actual amount of consumption. By assigning points based on quantity of consumption for each food item, our scoring system is continuously scaled and normally distributed. Since the scoring system in the present study only assessed relative adherence to each of the four ‘Blood-Type’ diets, we could not determine the absolute number of people who strictly followed any of the diets. However, the observed results showed that even relatively high adherence to Type-A, Type-AB and Type-O diets were associated with favorable levels of cardiometabolic disease risk factors, albeit in an ABO-independent manner. These associations were consistent with previous studies examining similar dietary patterns and cardiometabolic risk factors , , .
In summary, the present study is the first to test the validity of the ‘Blood-Type’ diet and we showed that adherence to certain diets is associated with some favorable cardiometabolic disease risk profiles. This may explain anecdotal evidence supporting these diets, which are generally prudent diets that reflect healthy eating habits. However, the findings showed that the observed associations were independent of ABO blood group and, therefore, the findings do not support the ‘Blood-Type’ diet hypothesis.
The food list was retrieved from the FFQ database of Toronto Nutrigenomics and Health Study. The “+” signs indicate the foods that are recommended for the blood group. The “-” signs indicate the food to avoid for the blood group. The “/” signs indicate the food that are neutral.
Conceived and designed the experiments: AE-S. Performed the experiments: JW. Analyzed the data: JW. Contributed reagents/materials/analysis tools: JW BG-B DN. Wrote the paper: JW. Assisted with the statistical analysis: BG-B. Assisted in data collection and study coordination: DN. Contributed to the manuscript revision for important intellectual content: BG-B DN.
- 1.D’Adamo P, Whitney C (1996) Eat Right 4 Your Type: The individualized diet solution to staying healthy, living longer & achieving your ideal weight. New York: Putnam.
- 2.D’Adamo P, Whitney C (2012) EAT RIGHT FOR YOUR TYPE. OFFICAL WEBSITE OF DR. PETER D’ADAMO & THE BLOOD TYPE DIET. Hoop-La-Joop, LLC, Inc.
- 3.Ghazarian H, Idoni B, Oppenheimer SB (2011) A glycobiology review: carbohydrates, lectins and implications in cancer therapeutics. Acta Histochem 113: 236–247. doi: 10.1016/j.acthis.2010.02.004
- 4.Wolpin BM, Kraft P, Gross M, Helzlsouer K, Bueno-de-Mesquita HB, et al. (2010) Pancreatic cancer risk and ABO blood group alleles: results from the pancreatic cancer cohort consortium. Cancer Res 70: 1015–1023. doi: 10.1158/0008-5472.can-09-2993
- 5.Aird I, Bentall HH, Roberts JA (1953) A relationship between cancer of stomach and the ABO blood groups. Br Med J 1: 799–801. doi: 10.1136/bmj.1.4814.799
- 6.Xie J, Qureshi AA, Li Y, Han J (2010) ABO blood group and incidence of skin cancer. PLoS One 5: e11972. doi: 10.1371/journal.pone.0011972
- 7.Gates MA, Wolpin BM, Cramer DW, Hankinson SE, Tworoger SS (2011) ABO blood group and incidence of epithelial ovarian cancer. Int J Cancer 128: 482–486. doi: 10.1002/ijc.25339
- 8.Rowe JA, Handel IG, Thera MA, Deans AM, Lyke KE, et al. (2007) Blood group O protects against severe Plasmodium falciparum malaria through the mechanism of reduced rosetting. Proc Natl Acad Sci U S A 104: 17471–17476. doi: 10.1073/pnas.0705390104
- 9.Glass RI, Holmgren J, Haley CE, Khan MR, Svennerholm AM, et al. (1985) Predisposition for cholera of individuals with O blood group. Possible evolutionary significance. Am J Epidemiol 121: 791–796.
- 10.Jenkins PV, O’Donnell JS (2006) ABO blood group determines plasma von Willebrand factor levels: a biologic function after all? Transfusion 46: 1836–1844. doi: 10.1111/j.1537-2995.2006.00975.x
- 11.Wu O, Bayoumi N, Vickers MA, Clark P (2008) ABO(H) blood groups and vascular disease: a systematic review and meta-analysis. J Thromb Haemost 6: 62–69. doi: 10.1111/j.1538-7836.2007.02818.x
- 12.Paterson AD, Lopes-Virella MF, Waggott D, Boright AP, Hosseini SM, et al. (2009) Genome-wide association identifies the ABO blood group as a major locus associated with serum levels of soluble E-selectin. Arterioscler Thromb Vasc Biol 29: 1958–1967. doi: 10.1161/atvbaha.109.192971
- 13.Qi L, Cornelis MC, Kraft P, Jensen M, van Dam RM, et al. (2010) Genetic variants in ABO blood group region, plasma soluble E-selectin levels and risk of type 2 diabetes. Hum Mol Genet 19: 1856–1862. doi: 10.1093/hmg/ddq057
- 14.Cusack L, De Buck E, Compernolle V, Vandekerckhove P (2013) Blood type diets lack supporting evidence: a systematic review. Am J Clin Nutr 98: 99–104. doi: 10.3945/ajcn.113.058693
- 15.Cahill L, Corey PN, El-Sohemy A (2009) Vitamin C deficiency in a population of young Canadian adults. Am J Epidemiol 170: 464–471. doi: 10.1093/aje/kwp156
- 16.Garcia-Bailo B, Brenner DR, Nielsen D, Lee HJ, Domanski D, et al. (2012) Dietary patterns and ethnicity are associated with distinct plasma proteomic groups. Am J Clin Nutr 95: 352–361. doi: 10.3945/ajcn.111.022657
- 17.Ainsworth BE, Haskell WL, Leon AS, Jacobs DR Jr, Montoye HJ, et al. (1993) Compendium of physical activities: classification of energy costs of human physical activities. Med Sci Sports Exerc 25: 71–80. doi: 10.1249/00005768-199301000-00011
- 18.Yamamoto F, Cid E, Yamamoto M, Blancher A (2012) ABO research in the modern era of genomics. Transfus Med Rev 26: 103–118. doi: 10.1016/j.tmrv.2011.08.002
- 19.Craig WJ (2009) Health effects of vegan diets. Am J Clin Nutr 89: 1627S–1633S. doi: 10.3945/ajcn.2009.26736n
- 20.Fung TT, Stampfer MJ, Manson JE, Rexrode KM, Willett WC, et al. (2004) Prospective study of major dietary patterns and stroke risk in women. Stroke 35: 2014–2019. doi: 10.1161/01.str.0000135762.89154.92
- 21.Fung TT, Willett WC, Stampfer MJ, Manson JE, Hu FB (2001) Dietary patterns and the risk of coronary heart disease in women. Arch Intern Med 161: 1857–1862. doi: 10.1001/archinte.161.15.1857
- 22.Steffen LM, Kroenke CH, Yu X, Pereira MA, Slattery ML, et al.. (2005) Associations of plant food, dairy product, and meat intakes with 15-y incidence of elevated blood pressure in young black and white adults: the Coronary Artery Risk Development in Young Adults (CARDIA) Study. Am J Clin Nutr 82: : 1169–1177; quiz 1363–1164.
- 23.van Dam RM, Grievink L, Ocke MC, Feskens EJ (2003) Patterns of food consumption and risk factors for cardiovascular disease in the general Dutch population. Am J Clin Nutr 77: 1156–1163.
- 24.Nordmann AJ, Nordmann A, Briel M, Keller U, Yancy WS Jr, et al. (2006) Effects of low-carbohydrate vs low-fat diets on weight loss and cardiovascular risk factors: a meta-analysis of randomized controlled trials. Arch Intern Med 166: 285–293. doi: 10.1001/archinte.166.3.285
- 25.Hu T, Mills KT, Yao L, Demanelis K, Eloustaz M, et al. (2012) Effects of low-carbohydrate diets versus low-fat diets on metabolic risk factors: a meta-analysis of randomized controlled clinical trials. Am J Epidemiol 176 Suppl 7S44–54. doi: 10.1093/aje/kws264
- 26.Santos FL, Esteves SS, da Costa Pereira A, Yancy WS Jr, Nunes JP (2012) Systematic review and meta-analysis of clinical trials of the effects of low carbohydrate diets on cardiovascular risk factors. Obes Rev 13: 1048–1066. doi: 10.1111/j.1467-789x.2012.01021.x
- 27.Stern L, Iqbal N, Seshadri P, Chicano KL, Daily DA, et al. (2004) The effects of low-carbohydrate versus conventional weight loss diets in severely obese adults: one-year follow-up of a randomized trial. Ann Intern Med 140: 778–785. doi: 10.7326/0003-4819-140-10-200405180-00007
- 28.Saitou N, Yamamoto F (1997) Evolution of primate ABO blood group genes and their homologous genes. Mol Biol Evol 14: 399–411. doi: 10.1093/oxfordjournals.molbev.a025776
- 29.Calafell F, Roubinet F, Ramirez-Soriano A, Saitou N, Bertranpetit J, et al. (2008) Evolutionary dynamics of the human ABO gene. Hum Genet 124: 123–135. doi: 10.1007/s00439-008-0530-8
- 30.Nachbar MS, Oppenheim JD (1980) Lectins in the United States diet: a survey of lectins in commonly consumed foods and a review of the literature. Am J Clin Nutr 33: 2338–2345.
- 31.Subar AF, Thompson FE, Kipnis V, Midthune D, Hurwitz P, et al. (2001) Comparative validation of the Block, Willett, and National Cancer Institute food frequency questionnaires : the Eating at America’s Table Study. Am J Epidemiol 154: 1089–1099. doi: 10.1093/aje/154.12.1089
- 32.Mourant AE, Kopec AC, Domaniewska-Sobczak K (1976) The Distribution of the Human Blood Groups and Other Polymorphisms. London: Oxford University Press.
- 33.Liese AD, Bortsov A, Gunther AL, Dabelea D, Reynolds K, et al. (2011) Association of DASH diet with cardiovascular risk factors in youth with diabetes mellitus: the SEARCH for Diabetes in Youth study. Circulation 123: 1410–1417. doi: 10.1161/circulationaha.110.955922
- 34.Patterson E, Larsson SC, Wolk A, Akesson A (2013) Association between dairy food consumption and risk of myocardial infarction in women differs by type of dairy food. J Nutr 143: 74–79. doi: 10.3945/jn.112.166330