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celiac disease affects 1 in 100 & the gfp matrix shows how ... - what chinese restaurant dishes are gluten free

by:Two Eight     2019-09-09
celiac disease affects 1 in 100 & the gfp matrix shows how ...  -  what chinese restaurant dishes are gluten free
Gluten Free demand in the US is lower than in Canada and Australia, but higher than in Japan.
The gluten free matrix shows how the demand for gluten free food and the value of luxury goods change due to community wealth.
In this article, gluten free studies show that: this study brings together all previous articles on the green fluorescent protein matrix Research and the green fluorescent protein website, and is based on gluten produced in December 2008.
The analysis compares communities in the Americas, Europe and Asia.
Communities are defined as specific language sections within a country.
Most markets in most countries are defined by their existing language search and English search.
To help with the analysis, the gluten-related search terms are divided into seven groups, as shown below.
The detailed statistical analysis uses only the first 50 search terms, but in most cases these 50 words account for 95% of all.
Gluten component: Another major concept in this study was the development of a term called "adjusted abdominal search ".
This value is based on the original tendon search volume) explain the Internet usage in a country and the total amount of possible search engine gluten queries (based on Google's market share in a specific country ).
So this adjusted value estimates the entire gluten search as if 100% of a country had Internet access and all search engine results were used.
This intermediate value is then divided by 100 to get the adjusted abdominal search value for each month.
It is assumed that the average milk fat rate of 100 people (diagnosed and undiagnosed) is about 1.
Therefore, this hypothesis value estimates the average number of times a lacerata searches for gluten-free products per month in a community, assuming that all lacerata searches are the case.
Please note that the main difference in English spelling in all countries is whether they use diarrhea (UK derived) or diarrhea (US ).
While it is found that the number of original searches per population can be used as a rough guide to their level of development, there are also several exceptions.
It was found that in very low (third layer) and high original search locations (first layer), a pattern appeared in the proportion of search groups.
See below: TIER1 features the main classification of this group is the high original search results (search/overall ).
The group includes: Australia (0. 0218), US (0. 0123);
English in Canada (0. 0175); UK (0. 0135);
English in Singapore (0. 02730).
The outstanding results of Singapore are in part due to the very high economic achievement (per capita GDP) of these countries and the very high use of Telecom (see the Asian green fluorescent protein matrix article ).
At the end of the high raw search end of the spectrum (and the high-adjusted diarrhea search), it was found that the proportion of ordinary gluten searches for KPIs was high compared to other groups.
It was also found that most of these searches are core generic terms such as: gluten, gluten free foods, gluten free products, etc, and these generic searches, usually two terms account for 90% or more of the entire group search.
Of the top 50 search terms, there are usually more than a dozen generic terms as well.
While the first two terms of several tertiary communities account for a high proportion of the group, the group usually has only five or fewer terms.
The second high group is usually the thecac group.
As with the general population, these terms are often core terms such as diarrhea, gluten intolerance, etc.
In the top 50 searches, the average proportion of specific food groups in seven is very low.
It is speculated that the first two groups accounted for 70% to 80% of the top 50 searches because of the high Internet penetration rate and high economic wealth of these communities in the general group, in these countries, high demand created a large number of gluten sites.
Gluten specific sites, like gluten shopping centers, have internal search capabilities that people can use to find the gluten information they want.
However, in less developed countries, these large websites may not exist, and people have learned to use unique search terms of three or four words to find what they want from the search engine stage.
The proportion of breast diarrhea group searches is high, and it is likely that the newly diagnosed and the elderly diagnosed as trying to find out if the disease has undergone a new medical breakthrough.
Similarly, core terms often dominate the group, as there are enough dedicated websites that contain diarrhea to provide answers that people are looking.
What food does the first-level community search?
The table below shows the bread (1. 6);
Almost always the first and/or second search term.
Then the next three most popular specific foods are cakes (2. 5), dairy (3. 5) and pizza (3. 8).
The main classification of this group on the third level is that the original search results of each group are very low.
The group is in Spanish from the United States (0. 0011);
Spanish in Mexico (0. 0004);
Brazilian Portuguese (0. 006);
Simplified Chinese (0. 009);
Indian Hindi (0. 0004);
Indonesia India (0. 0008).
As can be seen from the table, the average Common search ratio of the fourth-tier community is 32% (compared with the first-tier 58% ).
Compared to the first-level community, the average proportion of specific food groups is three times that of 22%.
Of the particular foods, the highest average Grade 4 is: Cake (1. 3), pizza (2. 0), cookies (2. 3), flour (2. 7), bread (3. 3), corn (3. 5), oatmeal (3.
These communities are developing gluten free markets.
Their original search is located between the first and third tier communities.
In the charts of the original or adjusted abdominal search and GDP or other similar indicators, these communities form a bridge between the first and third level communities.
While some second or third tier communities seem to have high generic searches, a large part of them are for non-
Core terms such as gluten free breakfast, gluten free snacks, gf desserts, gf gifts, etc.
Such low markets these markets exist in highly developed countries (such as first-level communities), and the proportion of ordinary gluten searches (such as first-level markets) with very low original gluten searches (such as third-level communities) is very high.
Three classic examples of the secondary community are in-service language searches in Germany, France and Spain.
It can be seen that the average value of the original search is 0.
0016, the average percentage of core generic terms is 81% (much higher than the average percentage of the first-level community) and 6% for specific foods-
From the first a very nearly.
General of special food looking for similar level months community.
In France, for example, the first three foods searched by French-speaking people are: gluten free flour, oatmeal and rye flour.
Assuming that every population in the European Community has a typical single ratio, a low original search is an anomaly.
The Internet penetration rate in these communities is high, and Google's market share is relatively high. Therefore, the low share is likely due to low diagnosis within the community.
The wheat and gluten consumed through bread and pasta in these areas is still relatively high, so there is either something else in their diet that prevents diarrhea from happening, or they find their gluten products in other ways.
These are the performance of supermarkets.
In the original search of each population, they look like the third tier community, that is, they have very low Search values, but when adjusted according to Internet penetration and Google share, they have too high a monthly value for abdominal search.
Often, unlike secondary markets, they are developing communities with relatively low GDP per capita.
The main examples of supermarkets are Russian English, Chinese traditional English and Indonesian English. The average original search value is 0.
0035, but these are very high search values converted to 5 areola. 4.
This means that the search volume of these populous countries is relatively low, and the Internet penetration rate is also low.
When adjusted to Internet penetration and Google's market share, they have the highest APIs in search in any community.
The average search ratio of supermarkets is often lower than Level 1 or even Level 3, and the specific food search ratio is between Level 1 and Level 3.
These super communities are often characterized by smaller English-speaking communities in larger non-English-speaking countries with lower economic wealth.
The proportion of people who have access to enhanced health care in these enclave is likely to be higher than the normal proportion (diagnosis first) their relative wealth makes their gluten-free taste more exotic/luxurious than the first-class community.
For example, the most popular Russian English-specific food, sorted by search size, is: pizza;
Gluten free beer
Gluten free cake
Gluten free muffins.
Similarly, the Indonesian English search was searched in order of size: gluten free pizza, gluten free pasta;
Gluten free muffins and flour.
Global conclusion the original search and the adjusted abdominal search results show a linear relationship between the two parameters.
While this may be predictable, this chart shows that Russia, China and Indonesia are anomalies in this trend.
As mentioned earlier, what these places have in common is that they all have a very large population, are developing countries, and the Internet penetration rate is low.
The supermarket field section above discusses the reasons for these outliers, but one of the most useful things is to see how many developed and developing communities are gathered at the undeveloped market end of this chart.
Although the markets in Australia, the US and Singapore have not fully developed (there are still a large number of people who have not been diagnosed --
Well below 1 of the 100 forecast), which shows that there is also a lot of room for development in these markets.
Since diarrhea is a disease with serious medical consequences for patients, it is surprising that very developed countries such as France, Germany and Italy should have such low gluten demand.
More notably, the effect of the chart on adjusted abdominal values and per capita GDP led to a strong log trend.
Ignoring the impact of abnormal hypermarkets such as Russia, China and Indonesia, it can be seen that with the increase of abdominal search values, most countries are in a steady downward arc.
This clearly shows that wealth (per capita GDP) is a clear indicator of gluten-free demand and/or diarrhea diagnosis for most analyzed countries.
Although India and Mexico may also deviate slightly from the log trend, it should be noted that the Internet penetration rate in these countries is very low, therefore, the adjustment factors to convert the first layer of original value to abdominal search value are more sensitive to the slight changes estimated by the Internet and Google media.
These relationships also suggest that, especially for countries with at least moderate internet penetration, knowing their GDP per capita might estimate their gluten free market development and/or diagnostic levels.
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