Using the Qiyas Method to prevent diabetes and obesity in the Middle East

One of the things we like to do at Qiyas is to start with a problem, a conundrum, or a complication that needs solving. One such problem is why do some people put on weight when they eat rice and others do not. For some people rice is a health food. Others put on weight quite easily when they often eat rice. We see this trend repeated with Qiyas clients. The other trend we identified was a clear rise in diabetes among people of Indian and Arab heritage. This trend is well studied in the medical literature. However, we wanted to understand when and why a rise in cases of diabetes occurred, and why some people were putting on weight when rice was a staple in their diet, while others were not. There appeared to be a link between these trends.

Ancestral heritage and food

In some populations rice and other starch-containing foods have been eaten for a long time. Peruvians and Bolivians have been eating potatoes for over 7,000 years; the Chinese have been farming rice for over 12,000 years (with recent evidence suggesting 15,000 years); Bangladeshis have been eating rice for 8,000 years; and South Indians have farmed rice for over 3,000 years. Generally we find that clients from these areas do not put on weight from eating rice. However, things become more interesting when we looked at people of Arab, Indian, and Pakistani heritage. Among this group of people we see both an increase in weight and diabetes from those who eat medium to large amounts of starch from carbohydrates, including rice.

We then delved into our database and started pulling historical data for these regions. Specifically, we looked at production figures for growing rice and import figures for importing rice.

The Arab Gulf States

Rice consumption

Take the example of the Arab Gulf States. Looking at import figures we find that rice started to be imported from the early 1900s. That means there was a period of tens of thousands of years where no rice was imported. Then, since 1975, corresponding to the oil boom, rice consumption (measured by import figures) has risen by 10% annually. This 10% annual increase is not enough to be noticed by individual families, because it’s a low increase, but over a 40 year period it adds up. If you placed the amount of rice a Gulf Arab family ate in 1950 over a whole year in a room, then put next to it the amount of rice a Gulf Arab family ate in 2016, the two piles would be very different in size.

Therefore, our historical data shows that rice was not being imported until very recently. The next question we asked was whether or not it was being grown in the region. For this we gathered reports from the time of British colonial rule, as good written records were kept. According to British accounts, the main carbohydrates for the Gulf and Bedu Arabs were from dairy products and fruit, and ancient wheat and barley for those in the Fertile Crescent. We then looked at figures and accounts for the production of rice. Apart from the Marsh Arabs in southern Iraq virtually no rice was being grown in the region.

From this data we determined that:

1. Rice was not part of the traditional Arab diet.
2. Little rice was imported or grown in the region before 1900.
3. Rice importation began in the early 1900s and increased dramatically with the oil boom.
4. Over the last 60 years there has been a huge increase in rice consumption.

Medical data and rice

When we looked at the medical data on rice we found that there was a direct association between high rice consumption and having type 2 diabetes in the region. Put this together with decreased activity levels and you have type 2 diabetes, obesity, and an increased risk for heart disease.

Genetic inheritance

Our historical datasets were revealing and they complemented our medical data. We then took a look at genetic data. One of the problems with relying solely on medical, epidemiological, and historical data is that while it reveals regional problems and solutions it doesn’t always address an individual. For example, through marriage, work, or other reasons some Gulf Arabs might have ancestral heritage from other parts of the Arab world, North Africa, or India. Some might not be aware of this family history.
One of the genes Qiyas tests for is the important AMY1 gene. To our knowledge no other provider tests for this gene. The AMY1 gene is hugely important. It is responsible for the digestion and metabolism of starch from carbohydrates. Some people have less copies of the AMY1 gene. This means that they do not digest the starch in carbohydrates such as rice very well. It also indicates that their ancestors did not eat very much starchy carbohydrates. Such people will gain weight and are at risk of inflammation and diabetes if they eat starch from carbohydrate.
A person’s AMY1 gene variation is a deep dive into their ancestral history. It explains how much carbohydrate a person should eat. It also explains why some people do well on a low-carbohydrate diet while other populations thrive on carbohydrates.

In identifying the number of AMY1 copies a person has we can give detailed recommendations on carbohydrate consumption helping to prevent obesity, diabetes, and cardiovascular disease.  We can tell you whether you should be on a low-carb diet or not.

The Qiyas Method

Therefore, the Qiyas Method uses a number of datasets to arrive at a comprehensive personalized health plan.

First, we identify health, disease, and lifestyle trends in different regions.

Second, we look at the historical diet, food patterns, activity, and lifestyle changes in specific regions and countries. Here our unique historical datasets, accounts for those regions, and their people are hugely important.

Third, we use genetic testing and data for a deep dive into an individual’s health. As we gather this genetic data it allows us to uniquely identify genetic influences and trends among specific regions and countries.

Fourth, we combine these results with traditional foods, lifestyles, and clinical recommendations to formulate a unique, highly Personalized Lifestyle Plan that is relevant to you, your heritage, and where you live.

As our various datasets get bigger we are able zoom in to specific areas within regions to further personalize healthcare advice. This prevents disease, helps with longevity, and ensures healthy people and populations.

What this shows is that historical data, epidemiological data, and genetic data all merge together to prevent disease and optimize health. This is the Qiyas Method.