Vitamin D deficiency is the most common among diabetes patients- Study
Sandy Verma January 31, 2025 02:24 AM

Delhi Delhi. According to the global analysis published in the British Medical Journal (BMJ) Nutrition Prevention and Health, vitamin D deficiency is the most common among diabetic patients, affecting more than 60 percent of people suffering from diabetes. Analysis based on 132 studies, including more than 52,000 participants between 1998 and 2023, also found that magnesium deficiency affects 42 percent of people suffering from diabetes, while 28 percent of people are suffering from iron deficiency . Researchers, including researchers at the Indian Health Management Research Institute (IIHMR) of Rajasthan, said that this study helps to assess the global spread of lack of micronutrients in people with type 2 diabetes – including vitamins required for healthy physical work and The level of minerals is very low.

The team found that women suffering from diabetes found a higher risk of lack of micronutrients than men, also known as “hidden hunger”. Authors reported that the risk factors of developing diabetes include genetic tendencies as well as environmental factors, such as sedentary lifestyle, unhealthy diet and obesity. Studies have shown that micronutrients have an important role in the development of diabetes, as they affect the path of glucose and the path of insulin.

However, the purpose of this study was to solve the contradictory evidence from previous studies, mainly focused on a specific micronutrient, the authors said, “He wrote,” Many micronutrients (vitamins, minerals and electrolytes in T2D patients ) The total prevalence of the deficiency was 45.30 percent. ”In addition, the prevalence in women with this condition was found to be higher than men – about 49 percent.

The analysis also found that the deficiency of vitamin B12 affects 29 percent diabetic patients globally and metformin, it is even more among those taking a common diabetic drug. The authors said that there is a need to carefully interpret the conclusions due to sample selection bias.

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