02514nas a2200313   4500000000100000008004100001260003700042653001400079653001400093653001900107653000900126653002500135653001100160653002100171653003100192100001400223700001300237700001600250700001300266700002100279700001300300700001500313700001500328245010600343856009800449300000700547520163200554022001402186       2025                            d  bPublic Library of Science (PLoS)10aVitamin C10aNutrition10aBlood pressure10aDiet10aMedical risk factors10aAnemia10aMachine learning10aMicronutrient deficiencies1 aAmewu EKA1 aAmaglo B1 aOsei-Poku P1 aAbakah A1 aKoney Shardow AL1 aWright L1 aKwarteng A1 aCrainey JL00aNutritional predictors of lymphatic filariasis progression: Insights from a machine learning approach  uhttps://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0320640&type=printable  a163 a<jats:p>Lymphatic filariasis (LF) is a mosquito-borne neglected tropical disease that causes disfiguring of the affected extremities, often leading to permanent disability and stigma. Described as a disease of poverty, the impact of socioeconomic indicators such as nutrition on LF remains largely unexplored. This cross-sectional study investigates nutritional predictors implicated in the progression of LF using machine learning methods in the Ahanta West Municipality, Ghana. There were 109 participants with a mean age of 50.72±13.8, and three-quarters being females. Only 14 (12.8%) each had comorbidities or LF-related wounds. Nutrition risk assessment showed 70.7% of participants were either malnourished or at risk of being malnourished. The prevalence of anemia was 84.0%. Dietary assessment indicates marked macro- and micronutrient intake with 98.2% protein, 75.2% fat, and 73.4% carbohydrate inadequacies. There were inadequate intakes of minerals: Calcium (100%), Potassium (91.7%) and Zinc (91.7%); and vitamins: Vitamin B12 (81.7%), Vitamin C (75.2%), Niacin (70.6%), and Vitamin B6 (68.8%). The decision tree and random forest models show vitamins C and K and blood pressure as the most important predictors of LF progression. Other predictors include body mass index, anemia, folate, and age. These findings suggest that maintaining healthy blood pressure and adequate intake of vitamins C and K may slow LF progression. This highlights the importance of nutritional intervention and underscores the need for integrated approaches that address nutritional deficiencies and LF management strategies.</jats:p>  a1932-6203