Phytonutrients: A Potential Role in Obesity (P08-047-19). (24th October 2019)

• Record Type: Journal Article
• Authors: Orgeron, Ryan; Pope, Janet; Erickson, Dawn; Green, Vicky
• Is Part Of: Current developments in nutrition. Volume 3(2019)Supplement 1
• Publication Date: 2019-10-24
• Subjects: Nutrition -- Periodicals; Nutritional Physiological Phenomena; Nutrition; Periodicals; Periodicals; Fulltext; Internet Resources; Periodicals; 612.3
• DOI: 10.1093/cdn/nzz044.P08-047-19
• Languages: English
• ISSNs: 2475-2991

Abstract

Abstract: Objectives: The primary aim of this study was to determine if phytonutrient intake, measured by the phytonutrient index (PI), is correlated with body composition in participants in Thibodaux, Louisiana. In addition, a second aim was to examine if intake of certain phytonutrient rich foods (based on green, reddish/purple, and yellow/orange colored fruits and vegetables) correlates with body fat percentage, waist circumference, and Body Mass Index (BMI). Methods: Participants Fifty (50) participants, ages18–54 selected. Exclusions were morbidly obese (BMI > 40 kg/m 2 ) and pregnant subjects. Procedures Body adiposity was measured by waist circumference, BMI, and fat percentage. Subjects completed three pass 24-hour food recalls (two weekdays/one weekend day. Each completed FFQ to determine the intake of the specific color. Caloric intake was estimated using ESHA software and used for PI calculation. PI formula estimated how much of the subject's energy intake was from phytonutrient rich foods (phytonutrient-rich kcal/total intake kcal) × 100.Phytonutrient rich foods primarily include fruits and vegetables, but also legumes, olive oil, and wine. Pearson correlation was used to assess correlations between phytonutrient index and body adiposity measures. Background data on every participant was gathered such as age, sex, health status, and race. IBM SPSS Statistics was used to analyze the data. Results considered statistically significant if p-value < 0.05. Results: The results showed a strong inverse correlation between PI and BMI (r = –0.753, P = 0.00), waist circumference (r = –0.730, P = 0.00), and body fat percentage (r = –0.701, P = 0.00). The intake of the specific phytonutrients and improved body composition did show a statistical significance. Individuals with higher weekly intakes of chlorophyll, carotenoid, and anthocyanin rich foods had better body composition in comparison to those who consumed less ( P < 0.05; F > Fcrit). Participants with various health conditions had an average PI lower than the population average (38.1 + 22.1). This was true of participants with type 2 diabetes (22 + 17.7), hypertension (17.4 + 11.6), hyperlipidemia (21.6 + 19.4), and osteoarthritis (24.3 + 27.4). Conclusions: The data in this study demonstrates that there is a strong correlation between higher phytonutrient intake and improved body composition (and disease prevalence). However this correlation remained consistent despite which type of phytonutrients were consumed. These findings conclude that overall diet quality seems to make the most difference, but the phytonutrients in fruits/vegetables are thought to be a key reason for those benefits. Funding Sources: Louisiana Tech University. Supporting Tables, Images and/or Graphs: