Health Effects of Street Vended Fresh Cut Fruits: A Randomised Control Trial in Bangladesh

Health Effects of Street Vended Fresh Cut Fruits DataDataset Overview:This dataset contains detailed clinical, demographic, microbiological, and experimental group information for participants who consumed guava fruits as part of a study investigating the potential association between fruit consumption, microbial contamination, and post-consumption symptoms.Files Included:This dataset comprises several Excel files from a study examining the association between guava fruit consumption, microbial contamination, and clinical symptoms. "Consumer only.xlsx" contains demographic and symptom data of guava consumers, while "Consumer with control.xlsx" includes both consumer and control participants, along with variables like fruit amount, CSCF, and HBN. "Control only.xlsx" provides baseline symptom data from non-consumers. "HAP__ANAP.xlsx" includes symptoms data in HAP (Having Acidity Problem) and ANAP (Apparently No Acidity Problem). "Microbial Contamination.xlsx" links symptoms with microbial findings, including TVC, S. aureus, and E. coli. Randomization details are recorded in "Randomized_300_participants.xlsx" and "Randomized_Participants_Reserved_Group.xlsx". Lastly, "TON.xlsx" tracks the time of symptom onset. Together, these files facilitate a comprehensive analysis of the impact of guava consumption and contamination on health outcomes.Purpose of the Dataset:The primary purpose of this dataset is to investigate the potential health impacts of consuming guava fruits sold by street vendors, with a specific focus on the relationship between microbial contamination and the onset of gastrointestinal and systemic symptoms. By integrating demographic data, symptom profiles, microbial test results, and randomized group assignments, the dataset enables comparative analysis between exposed (fruit consumers) and unexposed (controls) participants. It also allows for the assessment of temporal patterns in symptom onset and the identification of possible correlations between specific pathogens (e.g., E. coli, S. aureus) and clinical outcomes. Ultimately, the dataset supports public health evaluation of food safety risks associated with ready-to-eat fruits in urban environments.