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Record W6893583192 · doi:10.5281/zenodo.3550186

YOUR POOR EATING HABITS MAY CAUSE YOU CANCER, FINDS DON JURAVIN

2019· article· en· W6893583192 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2019
Typearticle
Languageen
FieldMedicine
TopicCancer Risks and Factors
Canadian institutionsnot available
Fundersnot available
KeywordsCancerObesityColorectal cancerWeight lossHealthy eatingCauses of cancer

Abstract

fetched live from OpenAlex

Don Karl Juravin (Holy Land Ministry, Florida, nonprofit org) found that poor eating habits not only cause obesity, but it also increases your chances of developing cancer. Bad eating habits could be deadly. Juravin, the world’s number one weight loss expert, warns against those who do not watch what they eat.\n\nHow is your diet affecting you?\n\nJuravin suggests that if you have bad eating habits, not only does it lead to obesity, but it could give you cancer.\n\nResearch Summary\n\n\n\t\n\t80,110 cancer cases per year are caused by poor diet\n\t\n\t\n\t5.2% of all invasive cancer cases stem from obesity and lack of nutrition\n\t\n\t\n\t38.3% of colon and rectal cancers are caused by a poor diet.\n\t\n\t\n\t20% of all cancers are linked to being obese. \n\t\n\t\n\t25 is the highest BMI not linked to cancer. Any higher BMI increases risk\n\t\n\t\n\tMen between the ages of 45 and 64 were most likely to develop diet-related cancer. \n\t\n\n\n \n\nCancer is just one of the risks obese people face with poor eating habits, according to studies. \n\nA study published in the JNCI Cancer Spectrum revealed over 80,000 new cancer cases among adults (Over 20) in the United States in 2015 were discovered to have a poor diet as a contributing factor.\n\n“This works out to 5.2% of all new invasive cancer cases among US adults in 2015,” said Dr. Fang Fang Zhang, a nutrition and cancer epidemiologist at Tufts University in Boston.\n\n“This proportion is comparable to the proportion of cancer burden attributable to alcohol,” she said.\n\nThe study included data on the dietary intake of adults in the United States between 2013 and 2016, which came from the National Health and Nutrition Examination Survey, as well as data on national cancer incidence in 2015 from the US Centers for Disease Control and Prevention.\n\nThe researchers used a comparative risk assessment model, which involved estimating the number of cancer cases associated with poor eating habits and helped evaluate how much this may impact the U.S. cancer burden. Those estimations were made using diet-cancer associations found in separate studies.\n\nAccording to Juravin, men between 45 and 64 years old and ethnic minorities, including blacks and Hispanics, had the highest proportion of diet-associated cancer burden compared with other groups, the researchers found.\n\n7 Dietary Factors Got Evaluated\n\nSeven dietary factors were researched: poor intake of vegetables, fruits, whole grains, and dairy products as well as higher consumption of processed or red meats. This also included sugary drinks like soda.\n\n“Low whole-grain consumption was associated with the largest cancer burden in the U.S, followed by low dairy intake, high processed-meat intake, low vegetable and fruit intake, high red meat intake and high intake of sugar-sweetened beverages,” Zhang said.\n\n“Previous studies provide strong evidence that high consumption of processed meat increases the risk of colorectal cancer and low consumption of whole grains increases the risk of colorectal cancer,” Zhang said. “However, our study quantified the number and proportion of new cancer cases that are attributable to poor diet at the national level.”\n\nResearchers found that colon and rectal cancers had the highest number, responsible for 38.3% of all diet-related cases.\n\n“Diet is among the few modifiable risk factors for cancer prevention,” Zhang said. “These findings underscore the need for reducing cancer burden and disparities in the U.S. by improving the intake of key food groups and nutrients.”\n\nYou Can Prevent Breast Cancer With Low-fat Eating Plans\n\nBreast cancer is less common in countries where the typical diet is plant-based and low in total fat (polyunsaturated fat and saturated fat). However, research on adult women in the United States hasn't found breast cancer risk to be related to dietary fat intake. One study suggests that girls who eat a high-fat diet during puberty, even if they don't become overweight or obese, may have a higher risk of developing breast cancer later in life.\n\nMore research is needed to better understand the effect of diet on breast cancer risk. But it is clear that calories do count and fat is a major source of calories. \n\nGo With Organic Foods Only\n\nUltra-processed foods are part of a fast-growing staple of the world’s diet. A 2016 study found that 60% of the calories in the average American diet come from this kind of food, and a 2017 study found that they make up half of the Canadian diet. They make up more than 50% of the UK diet, and more of the developing world is starting to eat this way.\n\nChanging your eating habits may prevent cancer by avoiding ultra-processed foods and instead choosing organic foods, research has shown.\n\nPeople who frequently eat organic foods lowered their overall risk of developing cancer, according to a study published last year in the medical journal JAMA Internal Medicine. Specifically, those who primarily ate organic foods were more likely to ward off non-Hodgkin lymphoma and postmenopausal breast cancer than those who rarely or never ate organic foods.\n\nAdditionally, according to a study published in the same journal in February, we face a 14% higher risk of early death with each 10% increase in the amount of ultra-processed foods we eat.\n\nBut people don’t want to make changes to their habits. \n\n“We are living in a fast world, and people are looking for convenient solutions. We are always stretched for time,” Nurgul Fitzgerald, an associate professor in the Department of Nutritional Sciences at Rutgers University, said earlier this year.\n\n“People are looking for quick solutions, a quickly made meal.”\n\nWhen selecting food, the taste is the No. 1 factor for most consumers, she said, but price and convenience are also important. The appeal of ultra-processed food is the “grab and go, ready to eat” ability.\n\nCredits\n\nResearch DOI: 10.5281/zenodo.3550186\n\nResearch by: Don Karl Juravin | Don Juravin tweets | Don Juravin videos | Don Juravin page | Don Karl Juravin Linkedin | Don Juravin education | Don Juravin Pinterest | Don Juravin images | Don Juravin blogs | Don Karl Juravin Reddit | Don Juravin scholar citation | JURAVIN RESEARCH | Don Juravin writer | Don Karl Juravin blog | Google+ | Ted Talks | Don Juravin docs | Don Juravin answers | Don Karl Juravin local | Juravin blogging | Juravin posts | Don Juravin Reviews |

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.490
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0320.006

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.049
GPT teacher head0.301
Teacher spread0.252 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2019
Admission routes1
Has abstractyes

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