Parkinson's disease prevention may 'begin at the dinner table'
- Denise Holsinger from York County can now walk again after doctors at WellSpan York Hospital placed a device that uses electrical impulses to help control her Parkinson's disease symptoms.
- Researchers examined extensive long-term dietary and health records from over 42,800 individuals who initially showed no signs of Parkinson’s disease to investigate connections between eating habits and early indicators of the condition.
- The study found that people consuming about 11 to 12 servings of ultraprocessed foods daily showed 2.5 times higher likelihood of experiencing three or more early Parkinson's symptoms.
- Dr. Xiang Gao, senior author of the study, indicated that consuming high amounts of processed foods may accelerate the appearance of early Parkinson’s symptoms and recommended reducing intake of such foods to promote better brain health.
- Although the study did not establish a direct increase in Parkinson's diagnosis, these findings suggest diet could influence neurodegeneration and prevention may start with nutrition choices.
53 Articles
53 Articles
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Parkinson's disease risk may rise 2.5-fold with frequent intake of ultraprocessed foods - worst offenders named
Consuming around 11 servings of ultraprocessed food daily could more than double the risk of developing early signs of Parkinson's disease, according to a new study.The research links foods such as sugary sodas, packaged snacks and hot dogs with prodromal Parkinson's symptoms.A single serving in the study was defined as eight ounces of diet or sugar-sweetened soda, one hot dog, a slice of packaged cake, a tablespoon of ketchup or a 1-ounce bag o…
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(MedPage Today) -- Long-term consumption of a high level of ultraprocessed foods was linked with an uptick in nonmotor prodromal Parkinson's disease symptoms, a prospective study of nearly 43,000 U.S. health professionals showed. When extreme...
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There is strong interest in using the gut microbiome for Parkinson’s disease (PD) diagnosis and treatment. However, a consensus on PD-associated microbiome features and a multi-study assessment of their diagnostic value is lacking. Here, we present a machine learning meta-analysis of PD microbiome studies of unprecedented scale (4489 samples). Within most studies, microbiome-based machine learning models accurately classify PD patients (average …
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