Introduction: Precision nutrition is an individualized approach to nutrition recommendations. The dietary guidelines advise Americans to consume 28g fiber/day/2000 kcals, but on average, Americans only consume 16g per day. Our gut microbiome is fed by fiber, and diet is the main driver in shaping the gut microbiome. From a precision nutrition approach, it’s important to understand how people respond differently to a variety of fiber sources to be able to create personalized nutrition recommendations to improve health outcomes. Objective: This study examined the feasibility of increasing fiber intake to 30g per day through emphasis of fruits and vegetables or whole grains. Methods: A cross over study design was used to examine the feasibility of increasing fiber intake in overweight adults in upstate New York who have low fiber intake. Participants were provided with food kits with high fiber foods containing either whole grains or fruits and vegetables. These foods were provided for two 4-week interventions. Personalized coaching sessions with a dietetic student were conducted to encourage compliance. Dietary intake was assessed using a validated instrument, The Automated Self-Administered 24-hour (ASA24) Dietary Assessment Tool and was completed by participants twice pre and post each intervention. A self report survey was designed to determine participant adherence to consuming the provided food kits and were completed by participants at the end of each intervention week. Body weight, BMI, and body fat percentage were measured using a bioelectrical impedance scale (Tanita, SC-240) pre and post both interventions. Descriptive statistics from the 24-hour dietary recall results were summarized with mean and standard deviation for servings of fruit (cup equivalents), servings of vegetables (cup equivalents), servings of whole grains (ounce equivalents), servings of refined grains (ounce equivalents), energy (kcal), protein (grams), fat (grams), and carbohydrates (grams). Body weight (lbs.), BMI (kg/m2), and body fat (%) results were summarized with mean and standard deviation. Linear regression models were developed using the 24-hour dietary recall results to evaluate pre and post intervention for servings of fruit (cup equivalents), servings of vegetables (cup equivalents), servings of whole grains (ounce equivalents), servings of refined grains (ounce equivalents), and dietary fiber intake (grams). Linear regression models were developed to evaluate pre and post intervention weight (lbs.) and body fat (%). Food kit adherence was determined using the self report survey results and were evaluated by averaging reported intake per food and per week. All statistical analysis was completed in RStudio. At the completion of the study, participants were able to participate in an optional phone interview to share feedback. Brief notes were written during these interviews and were used to develop a summary of participant feedback. Results: There was a total of 17 participants enrolled with two dropouts for a final sample size of 15 participants. All 17 participants were analyzed when possible. Of the 17 participants, 64.7% (n=11) were women, 88.2% (n=15) obtained a Bachelor’s or higher, and 76.5% (n=13) identified as white. Based on linear models from fruit and vegetable intake during the fruit and vegetable intervention, the change in servings of fruits was 0.28, which is a non significant increase (p < 0.23) in servings and the change in servings of vegetables was 1.26, which is a significant increase (p < 0.001) in servings. Based on linear models from whole grains and refined grains during the whole grain intervention, the change in servings of whole grains was 8.07, which is a significant increase (p < 0.001) in servings and the change in servings of refined grains was -2.78, which is a significant decrease (p < 0.03) in servings. Based on fiber intake linear models, the change in grams of dietary fiber during the FV was 22.7 grams which is a significant increase (p < 0.001) in grams of fiber and the change in grams of dietary fiber during the WG was 8.7 grams, which is a significant increase (p < 0.005) in grams of fiber. The change in weight during the FV was a gain one pound which is a non-significant change (p < 0.84) in weight. The change in weight during the WG was a loss of one pound which is a non-significant change (p < 0. 63) in weight. The change in body fat percentage during the FV was -0.8% which is a non-significant change (p < 0.63) in body fat percentage. The change in body fat percentage during the WG was +0.3% which is a non-significant change (p < 0.86) in body fat percentage. During the FV intervention, participants were most adherent during the first week with 82% adherence and each week decreased with the fourth week with 71% adherence. The lowest adherence was for week 3 of peas, with 50% adherence and the highest adherence was for week 4 of oranges with 91% adherence. During the WG intervention, participants were most adherent with the first week with 83% adherence and each week decreased with the fourth week with 66% adherence. The lowest adherence was for week 3 of popcorn, with 57% adherence and the highest adherence was for week 1 of bread with 95% adherence. Phone interviews were summarized with the main points voiced by participants including a desire for more variety of foods, less quantity of each food, more recipes, lack of cooking skills, and conflicting views of processed foods. Conclusion: This research has shown that it’s possible to increase fiber intake through the provision of fruits, vegetables, and whole grains to at least 30 grams of fiber per day. Participants were able to increase caloric intake without impacting their weight while also reducing their body fat percentage. With these important results, it’s incredibly important to continue finding ways for people to improve their fiber intake to reduce their risk for chronic disease. This study also evaluated common patterns of participant feedback to improve future studies. Notably, a wider variety of foods, less quantity of each food, and recipes could help participants be even more successful in increasing their dietary fiber intake in future fiber interventions.